Cooling control method and system of transformer

Abstract

The invention provides a cooling control method and system of a transformer, and belongs to the field of transformer cooling control. The method comprises the steps that the state information of the transformer is obtained, and the state information comprises the winding current and the top oil temperature of the transformer; calculating a load rate and a hot-spot temperature of the transformer based on the state information; fuzzifying the load rate and the hot spot temperature to obtain a fuzzy set; establishing a fuzzy control rule; adjusting parameters of a PID controller by combining the fuzzy set and a fuzzy control rule; using the adjusted PID controller to output a control signal; and performing cooling control on the transformer according to the control signal. According to the invention, the cooling control efficiency and stability can be improved.

Description

Technical Field

[0001] The present invention relates to the field of transformer cooling control, and in particular to a transformer cooling control method and system. Background Art

[0002] The cooling control method of the transformer refers to a control method that ensures that the transformer maintains an appropriate temperature during operation by adjusting and managing the transformer's cooling equipment (such as fans, oil pumps, etc.), thereby preventing damage to the transformer or affecting its performance due to overheating. It usually involves controlling the start and stop and adjustment of fans, cooling oil or other cooling equipment to avoid damage to the transformer due to overheating, while improving energy efficiency and extending equipment life. The cooling control method can be based on parameters such as temperature error and load rate, and combined with PID control, fuzzy control and other methods to achieve real-time adjustment.

[0003] When the transformer is running, heat will inevitably be generated due to the current flowing through the coil. As the load increases, the temperature inside the transformer will rise. If the temperature is too high, it may cause damage to the insulation material, shorten the service life of the transformer, and even cause equipment failure. In order to ensure the safe, stable and economical operation of the transformer, the oil level temperature, winding temperature, and load current of the transformer must be detected at any time, and cooling control must be performed to keep the transformer oil temperature within a reasonable range.

[0004] However, the existing cooling control method only considers a single variable to adjust the cooling equipment, ignoring the interaction between multiple variables, which can easily cause over-cooling or under-cooling. When controlling the cooling equipment, fixed PID gain parameters are usually used, which cannot effectively combine multiple variables for comprehensive control and cannot adapt to the needs of the system under different working conditions, resulting in insufficient control accuracy. Summary of the invention

[0005] The main purpose of the present invention is to provide a transformer cooling control method and system to solve the problem that a simple evaluation index for target tracking and matching has not yet appeared in the prior art, and effective guidance cannot be provided for the optimization of the target tracking and matching process, resulting in the inability to further improve the target tracking effect.

[0006] In order to achieve the above object, according to one aspect of the present invention, a transformer cooling control method is provided, comprising: S1: Obtaining status information of the transformer, wherein the status information includes a winding current and a top oil temperature of the transformer; S2: Calculate the load rate and hot spot temperature of the transformer based on the state information; S3: Fuzzifying the load rate and the hot spot temperature to obtain a fuzzy set; S4: Establish fuzzy control rules; S5: adjusting the parameters of the PID controller in combination with the fuzzy set and the fuzzy control rule; S6: Output a control signal using the adjusted PID controller; S7: Perform cooling control on the transformer according to the control signal.

[0007] Furthermore, the S1 is specifically: The current sensor is used to obtain the winding current of the transformer, and the temperature sensor is used to obtain the top oil temperature of the transformer.

[0008] Furthermore, the calculation formula of the hot spot temperature is specifically: ; ; ; ; ; ; Among them, θ H represents the hot spot temperature, θ A represents the ambient temperature, θ TO represents the top oil temperature, Δ represents the increment, Δθ H Indicates the temperature rise of the hot spot temperature relative to the top oil temperature, Δθ TO Indicates the temperature rise of the top oil temperature relative to the ambient temperature, Δθ H1 Indicates the temperature rise caused by the heat of the transformer winding, Δθ H2 Indicates the temperature rise caused by the heat taken away by the transformer cooling system, Δθ H1,u Indicates the time interval ends at Δθ H1 The value of Δθ H2,u Indicates the time interval ends at Δθ H2 The value of Δθ H1,i Denotes the time interval starting at Δθ H1 The value of Δθ H2,i Denotes the time interval starting at Δθ H2 The value of Dt is the time interval, D is the change, and DΔθ is H1 Denotes Δθ H1 The change in DΔθ H2 Denotes Δθ H2 The change in k 22 and k 21 represents the constant related to the transformer operation mode, Δθ Hr Indicates the rated increase in hot spot temperature relative to the top oil temperature, τ W represents the winding temperature time constant, τ orepresents the oil temperature time constant, L represents the load rate, and y represents a constant, which is a coefficient used to characterize the influence of the load rate on the hot spot temperature rise.

[0009] Furthermore, the calculation formula of the load rate is specifically: ; ; Where, L represents the load rate, I represents the effective value of the winding current, and I n Indicates rated current, I k represents the current value of k sampling points, , N represents the total number of sampling points.

[0010] Further, the fuzzy set includes a load rate fuzzy set and a hotspot temperature fuzzy set; The S3 specifically includes: S301: Fuzzify the load rate and the hot spot temperature to obtain corresponding fuzzy domain and fuzzy linguistic variables; S302: According to the fuzzy domain and the fuzzy linguistic variables, using a triangular membership distribution function, a fuzzy set of the load rate and a fuzzy set of the hotspot temperature are obtained.

[0011] Furthermore, the fuzzy domain of the load rate is specifically: ; Among them, L domain The fuzzy domain representing the load rate; The fuzzy linguistic variables of the load rate are specifically: {low load, medium load, high load}; The fuzzy domain of the hotspot temperature is specifically: ; Among them, T domain Fuzzy domain representing hotspot temperature; The fuzzy linguistic variables of the hot spot temperature are specifically: {Low, Medium, High}.

[0012] Furthermore, the fuzzy control rules specifically include: When the load rate is low load and the hot spot temperature is low temperature, the proportional gain, integral gain and differential gain are all reduced; When the load rate is high load and the hot spot temperature is high temperature, the proportional gain, integral gain and differential gain all increase; When the load rate is medium load and the hot spot temperature is medium temperature, the proportional gain, integral gain and differential gain remain unchanged; When the load rate is high and the hot spot temperature is low, the proportional gain increases, and the integral gain and the differential gain remain unchanged.

[0013] Furthermore, the S5 is specifically: Adjust the parameters of the PID controller according to the following formula: ; Among them, K P Represents proportional gain, K I Indicates the integral gain, K D Denotes the differential gain, K P0 , K I0 and K D0 Represents the initial proportional gain, initial integral gain and initial differential gain of the PID controller, β represents the adaptive adjustment factor, ΔK P , ΔK I and ΔK D They represent the adjustment amounts of proportional gain, integral gain and differential gain respectively.

[0014] Furthermore, the S6 is specifically: According to the following formula, the output control signal is: ; ; Among them, u(t) represents the control signal, e(t) represents the current error, d represents the differential operator, t represents the duration, θ target represents the target temperature, θ H Indicates the hot spot temperature.

[0015] According to one aspect of the present invention, there is provided a cooling control system for a transformer, comprising: processor; A memory having computer-readable instructions stored therein, wherein when the computer-readable instructions are executed by the processor, the above-mentioned transformer cooling control method is implemented.

[0016] In the present invention, by fuzzifying the load rate and hot spot temperature and establishing fuzzy control rules according to the load rate and hot spot temperature, the cooling requirements under different working conditions can be grasped more accurately, the limitations of single factor control are avoided, the control accuracy and the flexibility of system response are improved, and the adaptive gain of the PID controller is adjusted by fuzzy control so that the cooling system of the transformer can efficiently respond to different loads and temperature changes, avoiding untimely or excessive response caused by fixed gain, reducing energy waste and avoiding overcooling, and improving the efficiency and stability of cooling control.

[0017] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings: Figure 1 A schematic flow chart of a transformer cooling control method provided by an embodiment of the present invention is shown; Figure 2 A schematic structural diagram of a transformer cooling control system provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0022] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0023] Reference Manual Attached Figure 1 , shows a flow chart of a transformer cooling control method provided by an embodiment of the present invention.

[0024] An embodiment of the present invention provides a transformer cooling control method, comprising: S1: Obtain status information of the transformer, wherein the status information includes a winding current and a top oil temperature of the transformer.

[0025] Among them, the winding current is the current flowing through the winding part of the transformer. The winding current is a direct manifestation of the transformer load and directly affects the temperature and efficiency of the transformer. The top oil temperature is the top temperature of the transformer oil. The transformer oil plays a role in cooling and insulation. The temperature change can reflect the thermal load and cooling effect of the transformer.

[0026] It should be noted that obtaining the winding current and top oil temperature of the transformer as status information can monitor the workload and temperature status of the transformer in real time, providing accurate basic data for subsequent cooling control.

[0027] In a possible implementation manner, S1 specifically includes: The current sensor is used to obtain the winding current of the transformer, and the temperature sensor is used to obtain the top oil temperature of the transformer.

[0028] S2: Based on the status information, calculate the load factor and hot spot temperature of the transformer.

[0029] Among them, the load rate is the ratio between the actual working load of the transformer and its rated load, which is usually determined by calculating the ratio of the winding current to the rated current. It reflects the working intensity of the transformer. The hot spot temperature is the temperature of the hottest part inside the transformer, usually the local temperature of the winding or oil temperature. It is used to assess whether the transformer is in an overheated state, affecting the safety and life of the transformer.

[0030] It should be noted that by calculating the load rate and hot spot temperature, the working condition of the transformer can be accurately evaluated, providing a scientific basis for subsequent cooling control, helping to optimize the working state of the transformer, preventing failures caused by overload or overheating, and improving the operating safety and efficiency of the equipment.

[0031] In a possible implementation, the calculation formula for the hot spot temperature is specifically: ; ; ; ; ; ; Among them, θ H represents the hot spot temperature, θ A represents the ambient temperature, θ TO represents the top oil temperature, Δ represents the increment, Δθ H Indicates the temperature rise of the hot spot temperature relative to the top oil temperature, Δθ TO Indicates the temperature rise of the top oil temperature relative to the ambient temperature, Δθ H1 Indicates the temperature rise caused by the heat of the transformer winding, Δθ H2 Indicates the temperature rise caused by the heat taken away by the transformer cooling system, Δθ H1,u Indicates the time interval ends at Δθ H1 The value of Δθ H2,u Indicates the time interval ends at Δθ H2 The value of Δθ H1,i Denotes the time interval starting at Δθ H1 The value of Δθ H2,i Denotes the time interval starting at Δθ H2 The value of Dt is the time interval, D is the change, and DΔθ is H1 Denotes Δθ H1 The change in DΔθ H2 Denotes Δθ H2 The change in k 22 and k 21 represents the constant related to the transformer operation mode, Δθ Hr Indicates the rated increase in hot spot temperature relative to the top oil temperature, τ W represents the winding temperature time constant, τ o represents the oil temperature time constant, L represents the load rate, and y represents a constant, which is a coefficient used to characterize the influence of the load rate on the hot spot temperature rise.

[0032] In a possible implementation manner, the calculation formula of the load rate is specifically: ; ; Where, L represents the load rate, I represents the effective value of the winding current, and I n Indicates rated current, I k represents the current value of k sampling points, , N represents the total number of sampling points.

[0033] S3: Fuzzify the load rate and hot spot temperature to obtain a fuzzy set.

[0034] Among them, fuzzification is the process of converting clear input variables into fuzzy sets, and using membership functions to map certain values ​​to fuzzy sets to deal with uncertainty and ambiguity.

[0035] It should be noted that by fuzzifying the load rate and hot spot temperature, these two variables can be converted into fuzzy sets, so as to better cope with their possible changes and uncertainties. Fuzzy processing can convert these inputs into easy-to-process fuzzy linguistic variables, allowing the fuzzy control system to make more flexible and accurate decisions based on actual conditions.

[0036] In a possible implementation, the fuzzy set includes a load rate fuzzy set and a hot spot temperature fuzzy set.

[0037] S3 specifically includes sub-steps S301 and S302: S301: Fuzzify the load rate and the hot spot temperature to obtain corresponding fuzzy domains and fuzzy linguistic variables.

[0038] Among them, the fuzzy domain refers to the definition range of the fuzzy set. For the load rate and hot spot temperature, the fuzzy domain is the value range of these variables. The fuzzy language variable is a variable that expresses the fuzzy set through language description.

[0039] In a possible implementation, the fuzzy domain of the load rate is specifically: ; Among them, L domain A fuzzy domain representing the load factor.

[0040] The fuzzy linguistic variables of load rate are as follows: {Low load, Medium load, High load}.

[0041] In the present invention, the fuzzy linguistic variables of the load rate can be abbreviated as {LL, ML, HL}, where low load (LL) indicates that the transformer load is low, ranging from [0%, 40%], medium load (ML) indicates that the load is moderate, ranging from [30%, 70%], and high load (HL) indicates that the load is heavy, ranging from [60%, 100%].

[0042] The fuzzy domain of hot spot temperature is specifically: ; Among them, T domain A fuzzy domain representing the hotspot temperature.

[0043] The fuzzy linguistic variables of hot spot temperature are as follows: {Low, Medium, High}.

[0044] In the present invention, the fuzzy linguistic variables of hot spot temperature can be abbreviated as {LT, MT, HT}, low temperature (LT) means lower temperature, ranging from [30°C, 60°C], medium temperature (MT) means moderate temperature, ranging from [50°C, 100°C], and high temperature (HT) means higher temperature, ranging from [90°C, 150°C].

[0045] S302: According to the fuzzy domain and the fuzzy linguistic variables, using the triangle membership distribution function, a fuzzy set of the load rate and a fuzzy set of the hot spot temperature are obtained.

[0046] Among them, the triangular membership distribution function is a commonly used membership function. The shape of the triangle is used to represent the membership in the fuzzy set. The membership indicates the degree to which an input value belongs to a fuzzy set. The fuzzy set refers to dividing the values ​​of the input variables into different ranges (for example, low load, medium load, high load, etc.) according to a certain membership function, so that uncertainty and ambiguity can be handled.

[0047] It should be noted that by using the triangular membership distribution function for fuzzification processing, clear and easy-to-calculate memberships can be defined for the load factor and hot spot temperature, so that the fuzzy control system can make more accurate reasoning and control decisions.

[0048] The triangle membership distribution function is specifically: ; Among them, μ represents the triangular membership distribution function, x represents the input value, and a, b, and c represent the parameters of the fuzzy set, which determine the range of membership.

[0049] a is the left boundary, the membership starts from 0, b is the peak position, the membership is 1, and c is the right boundary, the membership decreases from 0.

[0050] In the present invention, the fuzzification of the load rate and the hot spot temperature specifically includes: Determine the load rate fuzzy subset and hot spot temperature fuzzy subset: Low load: {0%, 0%, 40%}, Medium load: {30%, 50%, 70%}, High load: {60%, 100%, 100%}.

[0051] Low temperature: {30℃, 30℃, 60℃}, medium temperature: {50℃, 75℃, 100℃}, high temperature: {90℃, 150℃, 150℃}.

[0052] The membership of load rate and hot spot temperature is calculated using the triangular membership distribution function: Assume the load factor is 65% and the hot spot temperature is 95°C.

[0053] Membership of low load: 65%>40%, μLL(65)=0.

[0054] Membership for medium load: .

[0055] High load membership: .

[0056] The fuzzy set of load rate is: {LL: 0, ML: 0.25, HL: 0.125}.

[0057] Membership of low temperature: 95℃>60℃, μTL(95)=0.

[0058] Medium temperature membership: .

[0059] High temperature membership: .

[0060] The fuzzy set of hot spot temperature is: T = {LT: 0, MT: 0.2, HT: 0.0833}.

[0061] S4: Establish fuzzy control rules.

[0062] It should be noted that by establishing fuzzy control rules, complex and fuzzy input information (such as load rate and temperature) can be converted into actionable control strategies, providing flexible decision-making basis, enabling the system to make appropriate adjustments in a changing environment, and effectively improving the stability and responsiveness of the system.

[0063] In a possible implementation, the fuzzy control rules specifically include: When the load rate is low load and the hot spot temperature is low temperature, the proportional gain, the integral gain, and the differential gain are all reduced.

[0064] When the load rate is a high load and the hot spot temperature is a high temperature, the proportional gain, the integral gain, and the differential gain all increase.

[0065] When the load rate is medium load and the hot spot temperature is medium temperature, the proportional gain, integral gain and differential gain remain unchanged.

[0066] When the load rate is high and the hot spot temperature is low, the proportional gain increases, and the integral gain and the differential gain remain unchanged.

[0067] S5: Combine fuzzy sets and fuzzy control rules to adjust the parameters of the PID controller.

[0068] Among them, PID controller refers to proportional-integral-differential controller, which is a commonly used feedback control system used to adjust the control signal. Through the combination of proportional, integral and differential parts, the PID controller can effectively adjust the system response.

[0069] It should be noted that by combining fuzzy sets and fuzzy control rules to adjust the parameters of the PID controller, the controller gain (proportional, integral and differential gain) can be dynamically optimized according to changes in load rate and hot spot temperature, thereby improving the accuracy and stability of cooling control, thereby extending the life of the equipment and optimizing energy utilization efficiency.

[0070] In a possible implementation, S5 is specifically: Adjust the parameters of the PID controller according to the following formula: ; Among them, K P Represents proportional gain, K I Indicates the integral gain, K D Denotes the differential gain, K P0 , K I0 and K D0 Represents the initial proportional gain, initial integral gain and initial differential gain of the PID controller, β represents the adaptive adjustment factor, ΔK P , ΔK I and ΔK D They represent the adjustment amounts of proportional gain, integral gain and differential gain respectively.

[0071] Specifically, β represents the adaptive adjustment factor, which dynamically adjusts the gain adjustment amount of the PID controller according to the change of the system state, affecting the gain value of the PID controller, so that the cooling system can adapt to the load and temperature changes in the operation of the transformer in real time. When the temperature of the transformer is too high, β is increased, and the gain of the PID controller is increased, thereby enhancing the cooling capacity. When the temperature is low, β is reduced to avoid overcooling.

[0072] S6: Output a control signal using the adjusted PID controller.

[0073] Among them, the control signal is the signal output by the PID controller, which represents the controller's instructions to the cooling equipment (such as fans, oil pumps, etc.). The strength of the control signal determines the working state of the cooling equipment.

[0074] It should be noted that the adjusted PID controller output control signal can optimize the response of the cooling system in real time according to the current error and system status (such as load, temperature, etc.), improve cooling efficiency, avoid excessive or insufficient cooling, and ensure that the transformer is at a safe operating temperature, extend equipment life and improve energy utilization.

[0075] In a possible implementation manner, S6 specifically includes: According to the following formula, the output control signal is: ; ; Among them, u(t) represents the control signal, e(t) represents the current error, d represents the differential operator, t represents the duration, θ target represents the target temperature, θ H Indicates the hot spot temperature.

[0076] S7: Control the cooling of the transformer according to the control signal.

[0077] In the present invention, intelligent cooling control of the transformer is realized by combining fuzzy control and PID adaptive adjustment. The current and oil temperature of the transformer are obtained in real time, the load rate and hot spot temperature are calculated, and fuzzy processing is performed. The gain of the PID controller is dynamically adjusted in combination with the fuzzy control rules, so as to accurately adjust the working state of the cooling equipment. The present invention can automatically optimize the cooling effect according to load and temperature changes, improve the system response speed, save energy, improve control accuracy, ensure the stable operation of the transformer at a safe temperature, and extend the life of the equipment.

[0078] From the above description, it can be seen that by fuzzifying the load rate and hot spot temperature and establishing fuzzy control rules based on the load rate and hot spot temperature, the cooling requirements under different working conditions can be grasped more accurately, avoiding the limitations of single factor control, improving the control accuracy and flexibility of system response, and using fuzzy control to adjust the adaptive gain of the PID controller so that the cooling system of the transformer can efficiently respond to different loads and temperature changes, avoiding untimely or over-reaction caused by fixed gain, reducing energy waste and avoiding over-cooling, and improving the efficiency and stability of cooling control.

[0079] Reference Manual Attached Figure 2 , shows a schematic structural diagram of a transformer cooling control system provided in an embodiment of the present invention.

[0080] The embodiment of the present invention provides a transformer cooling control system 20, comprising: Processor 201; The memory 202 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 201, the above-mentioned transformer cooling control method is implemented.

[0081] From the above description, it can be seen that by fuzzifying the load rate and hot spot temperature and establishing fuzzy control rules based on the load rate and hot spot temperature, the cooling requirements under different working conditions can be grasped more accurately, avoiding the limitations of single factor control, improving the control accuracy and flexibility of system response, and using fuzzy control to adjust the adaptive gain of the PID controller so that the cooling system of the transformer can efficiently respond to different loads and temperature changes, avoiding untimely or over-reaction caused by fixed gain, reducing energy waste and avoiding over-cooling, and improving the efficiency and stability of cooling control.

[0082] Unless otherwise specifically stated, the relative arrangement of the parts and steps described in these embodiments, numerical expressions and numerical values ​​do not limit the scope of the present invention. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0083] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0084] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the devices or elements referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention. The directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0085] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A transformer cooling control method, characterized in that: include: S1: Obtaining status information of the transformer, wherein the status information includes a winding current and a top oil temperature of the transformer; S2: Calculating the load rate and hot spot temperature of the transformer based on the state information; S3: Fuzzifying the load rate and the hot spot temperature to obtain a fuzzy set; S4: Establish fuzzy control rules; S5: adjusting the parameters of the PID controller in combination with the fuzzy set and the fuzzy control rule; S6: Output a control signal using the adjusted PID controller; S7: performing cooling control on the transformer according to the control signal; The calculation formula of the hot spot temperature is specifically: ； ； ； ； ； ； Among them, θ H represents the hot spot temperature, θ A represents the ambient temperature, θ TO represents the top oil temperature, Δ represents the increment, Δθ H Indicates the temperature rise of the hot spot temperature relative to the top oil temperature, Δθ TO Indicates the temperature rise of the top oil temperature relative to the ambient temperature, Δθ H1 Indicates the temperature rise caused by the heat of the transformer winding, Δθ H2 Indicates the temperature rise caused by the heat taken away by the transformer cooling system, Δθ H1,u Indicates the time interval ends at Δθ H1 The value of Δθ H2,u Indicates the time interval ends at Δθ H2 The value of Δθ H1,i Denotes the time interval starting at Δθ H1 The value of Δθ H2,i Denotes the time interval starting at Δθ H2 The value of Dt is the time interval, D is the change, and DΔθ is H1 Denotes Δθ H1 The change in DΔθ H2 Denotes Δθ H2 The change in k 22 and k 21 represents the constant related to the transformer operation mode, Δθ Hr Indicates the rated increase in hot spot temperature relative to the top oil temperature, τ W represents the winding temperature time constant, τ o represents the oil temperature time constant, L represents the load rate, and y represents a constant, which is a coefficient used to characterize the influence of the load rate on the hot spot temperature rise.

2. The transformer cooling control method according to claim 1, characterized in that: The S1 is specifically: The current sensor is used to obtain the winding current of the transformer, and the temperature sensor is used to obtain the top oil temperature of the transformer.

3. The transformer cooling control method according to claim 1, characterized in that: The calculation formula of the load rate is specifically: ； ； Where, L represents the load rate, I represents the effective value of the winding current, and I n Indicates rated current, I k represents the current value of k sampling points, , N represents the total number of sampling points.

4. The transformer cooling control method according to claim 1, characterized in that: The fuzzy set includes a load rate fuzzy set and a hotspot temperature fuzzy set; The S3 specifically includes: S301: Fuzzify the load rate and the hot spot temperature to obtain corresponding fuzzy domain and fuzzy linguistic variables; S302: According to the fuzzy domain and the fuzzy linguistic variables, using a triangular membership distribution function, obtain the load rate fuzzy set and the hot spot temperature fuzzy set.

5. The transformer cooling control method according to claim 4, characterized in that: The fuzzy domain of the load rate is specifically: ； Among them, L domain The fuzzy domain representing the load rate; The fuzzy linguistic variables of the load rate are specifically: {low load, medium load, high load}; The fuzzy domain of the hotspot temperature is specifically: ； Among them, T domain Fuzzy domain representing hotspot temperature; The fuzzy linguistic variables of the hot spot temperature are specifically: {Low, Medium, High}.

6. The transformer cooling control method according to claim 1, characterized in that: The fuzzy control rules specifically include: When the load rate is low load and the hot spot temperature is low temperature, the proportional gain, integral gain and differential gain are all reduced; When the load rate is high load and the hot spot temperature is high temperature, the proportional gain, integral gain and differential gain all increase; When the load rate is medium load and the hot spot temperature is medium temperature, the proportional gain, integral gain and differential gain remain unchanged; When the load rate is high and the hot spot temperature is low, the proportional gain increases, and the integral gain and the differential gain remain unchanged.

7. The transformer cooling control method according to claim 1, characterized in that: The S5 is specifically: Adjust the parameters of the PID controller according to the following formula: ； Among them, K P Represents proportional gain, K I Indicates the integral gain, K D Denotes the differential gain, K P0 , K I0 and K D0 Represents the initial proportional gain, initial integral gain and initial differential gain of the PID controller, β represents the adaptive adjustment factor, ΔK P , ΔK I and ΔK D They represent the adjustment amounts of proportional gain, integral gain and differential gain respectively.

8. The transformer cooling control method according to claim 7, characterized in that: The S6 is specifically: According to the following formula, the output control signal is: ； ； Among them, u(t) represents the control signal, e(t) represents the current error, d represents the differential operator, t represents the duration, θ target represents the target temperature, θ H Indicates the hot spot temperature.

9. A cooling control system for a transformer, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the cooling control method for the transformer according to any one of claims 1 to 8 is implemented.

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