A method and system for assessing transformer lifespan

Abstract

This invention relates to the field of power equipment monitoring technology, and more particularly to a method and system for assessing transformer lifespan. The method includes: acquiring the temperature values ​​at various times during the current assessment period from multiple temperature measurement points equidistantly distributed along the transformer windings; determining a rate factor characterizing the aging rate of each temperature measurement point at that time; determining a gradient factor characterizing the degree of temperature change in the area to which each temperature measurement point belongs at that time; determining the cumulative equivalent aging time of each temperature measurement point during the current assessment period; and determining the remaining lifespan of the transformer after the current assessment period. This invention, through distributed temperature measurement and the introduction of both rate and gradient factors, provides a refined assessment of insulation aging; by accumulating the equivalent aging time, it achieves a dynamic and accurate assessment of transformer lifespan, significantly improving reliability and providing a scientific basis for preventative maintenance.

Description

Technical Field

[0001] This invention relates to the field of power equipment monitoring technology, and in particular to a method and system for assessing transformer lifespan. Background Technology

[0002] As a critical hub in the power grid, the safe and stable operation of transformers is essential to the reliability of the entire power system. Among the many factors affecting transformer lifespan, the health of the insulation system is decisive, and operating temperature is the primary accelerating factor driving the aging of insulation materials. Prolonged exposure to high temperatures causes cellulose degradation in the transformer's internal insulation paper, deterioration of the physical and chemical properties of the insulating oil, and weakening of its overall mechanical strength. These irreversible aging processes significantly shorten the transformer's effective service life.

[0003] With the increasing demands of modern power grids on transmission and distribution capacity, transformers are experiencing increasingly severe load fluctuations and more complex operating environments. This leads to significant dynamics and non-uniformity in their internal temperature distribution. In recent years, the introduction of advanced sensing technologies such as fiber optic winding temperature measurement devices has enabled the acquisition of detailed temperature distributions along transformer windings, providing a sufficient data foundation for refined condition assessment.

[0004] However, most current mainstream transformer life assessments in the industry still rely on traditional, simplified temperature monitoring methods, such as calculations based solely on top-layer oil temperature and average oil temperature data. While these traditional methods are simple to deploy, their inherent limitations are also significant: First, traditional methods cannot capture localized hot spots caused by factors such as poor oil flow, inter-turn short-circuit risks, or localized heat dissipation defects, which are precisely the weakest links in the insulation system; second, a single average temperature or representative point temperature masks the complex temperature gradient distribution within the windings, failing to reflect the additional stress on the insulation material caused by drastic temperature changes, leading to an underestimation of aging risks and thus affecting the accuracy of transformer life assessments. Summary of the Invention

[0005] To address the technical problem that existing transformer life assessment methods rely on single-point or average temperatures, resulting in low accuracy and an inability to accurately reflect the effects of local hot spots and temperature gradients, thus affecting the accuracy of transformer life assessment, this invention provides a transformer life assessment method and system.

[0006] In a first aspect, the present invention provides a method for assessing the lifespan of a transformer, employing the following technical solution:

[0007] A transformer life assessment method includes: acquiring the temperature values ​​of multiple temperature measuring points equidistantly arranged along the transformer windings at various times during the current assessment period; for each time point during the current assessment period, determining a rate factor characterizing the aging rate of each temperature measuring point at that time, based on the apparent activation energy, gas constant, temperature value corresponding to the ideal life of the transformer, and the temperature value of each temperature measuring point at that time; determining a gradient factor characterizing the degree of temperature change in the region to which each temperature measuring point belongs at that time, based on the temperature value difference between adjacent temperature measuring points before and after each temperature measuring point at that time, and the distance between adjacent temperature measuring points before and after each temperature measuring point; determining the cumulative equivalent aging time of each temperature measuring point during the current assessment period based on the rate factor and gradient factor at each time point during the assessment period; and determining the remaining life of the transformer after the current assessment period based on the remaining life of the transformer after the previous assessment period, the cumulative equivalent aging time, and the rate factor.

[0008] This invention achieves comprehensive monitoring of the transformer's temperature field by equidistantly arranging multiple temperature measurement points along the transformer windings. This overcomes the monitoring blind spots caused by traditional methods relying solely on top-layer or average oil temperature. It effectively captures local hotspots and temperature gradient distribution within the windings, providing a richer temperature data foundation for accurate insulation aging assessment. By introducing a dual assessment mechanism of rate factor and gradient factor, it achieves refined modeling of the transformer aging process. The rate factor, based on physical parameters such as the apparent activation energy of the insulation material, accurately reflects the aging rate of the insulation material under different temperature conditions. The gradient factor quantifies the severity of temperature changes through the temperature difference and distance relationship between adjacent measurement points, effectively identifying areas with high aging risk. Through the calculation of cumulative equivalent aging time, it comprehensively considers the cumulative effects of aging in both time and space dimensions, achieving dynamic assessment of the overall transformer lifespan. This allows for timely detection of additional aging stress caused by local overheating and abnormal temperature gradients, avoiding the underestimation of aging risk by traditional methods. This significantly improves the accuracy and reliability of transformer lifespan assessment, providing a scientific basis for preventative maintenance and safe operation of transformers.

[0009] Furthermore, the temperature value is the temperature value after filtering and noise reduction.

[0010] Furthermore, the velocity factor satisfies:

[0011] In the formula, Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate The apparent activation energy of the insulating material used in transformers. The gas constant is This refers to the temperature value corresponding to the ideal lifespan of the transformer. Temperature measurement point At any moment Temperature value, It is a natural exponential function.

[0012] This invention constructs a rate factor calculation model using the exponential form of the Arrhenius equation, accurately reflecting the nonlinear relationship between the aging rate of insulating materials and temperature. Based on chemical reaction kinetics theory, this model has clear physical meaning and basis, and can accurately describe the activity level of molecular thermal motion in insulating materials under different temperature conditions. By introducing material characteristic parameters such as apparent activation energy and gas constant, the rate factor calculation exhibits good material adaptability. The introduction of the ideal lifespan corresponding temperature value provides a benchmark reference for aging rate assessment, facilitating comparison of aging degrees under different operating conditions. It can sensitively respond to temperature changes; when the temperature at the measurement point increases, the rate factor grows exponentially, accurately reflecting the accelerating effect of high temperatures on the aging of insulating materials. This provides a reliable theoretical basis for subsequent calculation of cumulative equivalent aging time, significantly improving the scientific rigor and accuracy of transformer lifespan assessment.

[0013] Furthermore, the gradient factor satisfies:

[0014] ;

[0015] In the formula, For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. The preset gradient sensitivity coefficient, and These are the temperature measurement points. The adjacent temperature measurement points at time Temperature value, The distance between two adjacent temperature measuring points. The maximum and minimum value normalization function, It is the absolute value symbol.

[0016] This invention constructs a quantitative model of gradient factor by calculating the ratio of the temperature difference between adjacent temperature measurement points to the distance, which can effectively reflect the degree of temperature change in the area where the temperature measurement point is located; thereby identifying dangerous areas with drastic temperature changes, providing an important basis for accurately assessing local aging risks. By combining gradient factor and speed factor, a comprehensive assessment of the transformer aging process is achieved, significantly improving the accuracy and reliability of life assessment.

[0017] Furthermore, the gradient sensitivity coefficient is preset based on the mechanical strength test data of the insulating material used in the transformer; for brittle materials in the insulating material, the value of the gradient sensitivity coefficient is greater than that for tough materials in the insulating material.

[0018] Furthermore, the gradient factor is used to amplify the aging assessment of areas with localized temperature anomalies.

[0019] Furthermore, the cumulative equivalent aging time satisfies:

[0020] In the formula, Temperature measurement point The cumulative equivalent aging time during the current assessment period Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. This represents the time micro-element of the current evaluation period.

[0021] This invention constructs a calculation model for cumulative equivalent aging time by integrating the product of the rate factor and the gradient factor over the time axis. It comprehensively considers the aging accumulation effect in both time and space dimensions. The rate factor reflects the influence of temperature on the aging rate, while the gradient factor reflects the aggravating effect of temperature gradient on local aging stress. The product of the two can accurately characterize the actual aging degree of the temperature measurement point under complex thermal environment. The integral calculation method can comprehensively reflect the aging accumulation process throughout the entire evaluation period, avoiding the random errors that may be caused by instantaneous temperature measurement. Through continuous time domain accumulation calculation, the aging assessment becomes more scientific and accurate, enabling timely detection of additional aging risks caused by local overheating and abnormal temperature gradients. This significantly improves the accuracy and practicality of transformer life assessment and provides important technical support for preventive maintenance and safe operation of equipment.

[0022] Further, determining the remaining lifespan of the transformer after the current evaluation period includes: for each temperature measurement point, determining the aging weight of that temperature measurement point among all temperature measurement points based on the speed factor; taking the sum of the products of the cumulative equivalent aging time of each temperature measurement point and the corresponding aging weight as the total equivalent aging consumption time of the transformer in the current evaluation period; and subtracting the remaining lifespan of the transformer after the previous evaluation period from the total equivalent aging consumption time to obtain the remaining lifespan of the transformer after the current evaluation period.

[0023] This invention determines the aging weight of each temperature measurement point through a speed factor, enabling differentiated assessment of aging risks at different locations. The aging weight reflects the importance of each temperature measurement point to the overall lifespan of the transformer, ensuring the scientific and rational nature of the lifespan assessment. The total equivalent aging time is calculated using a weighted summation method, comprehensively considering the cumulative equivalent aging time and relative importance of each temperature measurement point, avoiding assessment biases that may result from simple averaging, and accurately reflecting the overall aging state of the transformer. Furthermore, it enables dynamic updating and accurate prediction of the transformer's remaining lifespan. By calculating the difference between historical remaining lifespan and current aging consumption, it provides a quantitative scientific basis for equipment maintenance decisions, improving the accuracy and practicality of transformer lifespan assessment and providing crucial protection for the safe and stable operation of the power system.

[0024] Furthermore, the aging weight satisfies:

[0025] In the formula, Temperature measurement point Aging weights at all temperature measurement points Temperature measurement points used to characterize the transformer The maximum value of the rate factor of aging rate at all times within the current evaluation period. This represents the number of temperature measurement points.

[0026] Secondly, the present invention provides a transformer life assessment system, which adopts the following technical solution:

[0027] A transformer life assessment system includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned transformer life assessment method is implemented.

[0028] By adopting the above technical solution, a computer program for evaluating the lifespan of a transformer is generated and stored in a memory, so that it can be loaded and executed by a processor. A terminal device can then be made based on the memory and the processor for convenient use.

[0029] The present invention has the following technical effects:

[0030] (1) Breaking through the limitations of traditional reliance on top oil temperature or average oil temperature, multiple temperature measuring points are arranged at equal intervals along the winding to collect temperature data of each area in real time. Combined with the speed factor (calculated based on the activation energy of the insulation material, temperature value, etc.), the aging rate of each temperature measuring point is accurately quantified. This can effectively capture local hot spots caused by poor oil flow, inter-turn short circuit risk, or local heat dissipation defects, avoid the omission of weak links in the insulation system by traditional methods, and solve the problem of underestimation of aging risk caused by local high temperature.

[0031] (2) The gradient factor (calculated based on the temperature difference and distance between adjacent temperature measurement points) is introduced to characterize the degree of temperature change, which makes up for the shortcomings of traditional methods in masking the internal temperature gradient of the winding. The larger the temperature gradient, the more significant the thermal stress on the insulation material. The introduction of the gradient factor can accurately quantify the accelerating effect of this additional stress on aging, so that the life assessment not only considers the absolute temperature, but also incorporates the influence of dynamic temperature changes, which greatly improves the comprehensiveness and scientific nature of the assessment.

[0032] (3) By calculating the cumulative equivalent aging time of each temperature measurement point during the evaluation period (integrating the speed factor and gradient factor at each moment), the dynamic accumulation of aging contribution in different time periods and different areas is realized. Compared with the traditional static temperature evaluation mode, it can reflect the aging rate changes caused by load fluctuations, environmental changes and other factors in real time, accurately quantify dynamic effects such as "accelerated aging during high temperature periods and aggravated damage by drastic temperature changes", and make the remaining life calculation more in line with the actual aging process of the equipment.

[0033] (4) Based on accurate local aging data and cumulative equivalent aging time, the remaining life of the transformer can be scientifically updated, providing clear basis for operation and maintenance personnel. This helps to formulate targeted heat dissipation optimization, load adjustment or maintenance plans, avoid the risk of over-maintenance or neglect due to inaccurate assessment, significantly improve the reliability of transformer operation, reduce the probability of sudden failure, extend the effective service life of equipment, and reduce power system downtime losses. Attached Figure Description

[0034] Figure 1 This is a flowchart of a transformer life assessment method according to an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of the temperature data filtering effect in a transformer life assessment method according to an embodiment of the present invention.

[0036] Figure 3 This is a schematic diagram of the change in the velocity factor at each temperature measurement point in a transformer life assessment method according to an embodiment of the present invention.

[0037] Figure 4 This is a schematic diagram of the gradient factor changes at each temperature measurement point in a transformer life assessment method according to an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] This invention discloses a method for assessing the lifespan of a transformer, referring to... Figure 1 This includes steps S1-S5:

[0040] S1: Obtain the temperature values ​​at various times during the current evaluation period from multiple temperature measurement points equidistantly arranged along the transformer windings.

[0041] It's important to note that to initiate the evaluation process, it's crucial to first obtain precise, real-time temperature data of the transformer's internal windings. Unlike traditional methods, this step utilizes fiber optic winding temperature measurement devices to simultaneously collect temperature values ​​at multiple equidistant temperature measurement points along the surface or interior of the transformer windings (e.g., high-voltage or low-voltage windings). These measurement points cover the entire physical length of the windings, forming a one-dimensional temperature distribution profile. For example, for a large transformer, a temperature measurement point can be placed every 10 centimeters, resulting in temperature data from hundreds or more points. This full-space, high-density data acquisition method forms the basis for subsequent accurate evaluation, ensuring that potential localized abnormal temperature rises are detected and avoiding the risk of missing critical hotspot information due to sparse measurement points.

[0042] like Figure 2 As shown, specifically, the temperature value is the temperature value after being filtered (such as Kalman filtering) to remove noise.

[0043] S2: Determine the rate factor for each temperature measurement point of the transformer at that moment to characterize the aging rate.

[0044] It should be noted that the thermal aging of insulation materials is essentially a chemical reaction, and its rate follows the Arrhenius law: the aging rate increases exponentially with each increase in temperature. The aging rate of the core materials in a transformer insulation system is closely related to the operating temperature: prolonged high temperatures accelerate cellulose degradation and oil deterioration, while low temperatures significantly slow down this process. Therefore, this step introduces a rate factor to quantify the difference in insulation aging rate relative to the ideal state at different temperatures, providing a scientific basis for the subsequent cumulative calculation of lifespan consumption.

[0045] For each moment within the current evaluation period, based on the apparent activation energy of the insulation material used in the transformer (an inherent property of the material that reflects the energy threshold required to initiate its aging reaction, typically obtained through accelerated thermal aging tests, such as for kraft paper insulation), Typical values ​​in Left and right, need to be converted to when calculating. ), gas constant (a universal physical constant in thermodynamics) The ideal lifespan of the transformer corresponds to the temperature value (usually the design reference temperature, such as 60℃, at which the insulation material can reach its ideal lifespan), and the temperature value of each temperature measuring point at that moment (Arrhenius's law requires calculation based on absolute temperature, therefore the temperature value needs to be converted to absolute temperature, absolute temperature...). ) is the temperature value ( ) The rate factor is determined to characterize the aging rate of each temperature measurement point of the transformer at that moment.

[0046] Specifically, the velocity factor satisfies:

[0047] ;

[0048] In the formula, Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate The apparent activation energy of the insulating material used in transformers. The gas constant is This refers to the temperature value corresponding to the ideal lifespan of the transformer. Temperature measurement point At any moment Temperature value, It is a natural exponential function.

[0049] in, This represents the sensitivity coefficient of an insulating material to temperature changes. The larger the value, the stronger the thermal aging sensitivity of the insulating material; the more significant the effect of small temperature changes on the aging rate. The more easily it changes drastically with temperature fluctuations (increasing sharply at high temperatures and decreasing significantly at low temperatures); and vice versa. This represents the reciprocal of the absolute temperature corresponding to the ideal lifespan. The larger this value, the lower the ideal temperature (because absolute temperature is inversely proportional to its reciprocal). In this case, the probability of the actual operating temperature exceeding the ideal temperature is higher. It is easier for the value to be positive, resulting in a positive exponent term. The higher the value, the more likely it is to exceed 1 (i.e., accelerate aging); conversely, the lower the value, the more likely it is to exceed 1. Indicates temperature measurement point At any moment The absolute temperature value is the reciprocal of the temperature. The larger this value, the lower the actual temperature at the measuring point. The smaller the difference, or even if it becomes negative, the smaller or negative the exponent term will be. The higher the value, the easier it is for the value to be less than 1 (i.e., delay aging); conversely, the higher the value, the easier it is for the value to be less than 1.

[0050] like Figure 3As shown, the velocity factor at different temperature measurement points varies significantly with temperature changes. The velocity factor at temperature measurement points with higher temperatures increases significantly, reflecting the accelerated aging rate in high-temperature regions.

[0051] S3: Determine the gradient factor used to characterize the degree of temperature change in the region to which each temperature measurement point belongs at that moment.

[0052] It should be noted that the temperature distribution in transformer windings is not uniform. Local hotspots (such as inter-turn short circuits or oil flow blockages) may have significantly higher temperatures than the surrounding areas, but traditional single-point temperature measurement may miss these details. Furthermore, even if the temperature at a certain point does not reach the global maximum, if the temperature difference between it and adjacent areas is drastic (i.e., a large temperature gradient), it may be a high-risk point for insulation degradation. Such a gradient often indicates poor local heat dissipation or abnormal heating, which can lead to accelerated local aging of the insulation material over the long term. Therefore, this step constructs a local gradient amplification factor to assign a higher weight to the aging contribution of areas with steep temperature changes, making the assessment results more consistent with the actual risk distribution.

[0053] Based on the temperature difference between each temperature measuring point and the adjacent temperature measuring points at that moment (determined by the arc length order of the optical fiber on the winding, which refers to the physical order formed by the arc structure or winding path of the winding itself when it is laid out on the winding, simply put, it is the order in which the various temperature measuring points on the optical fiber are arranged along the length direction of the winding bend), and the distance between each temperature measuring point and the adjacent temperature measuring points, a gradient factor is determined to characterize the degree of temperature change in the region to which each temperature measuring point belongs at that moment.

[0054] Specifically, the gradient factor satisfies:

[0055] ;

[0056] In the formula, For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. The preset gradient sensitivity coefficient, and These are the temperature measurement points. The adjacent temperature measurement points at time Temperature value, The distance between two adjacent temperature measuring points. The maximum and minimum value normalization function, It is the absolute value symbol.

[0057] in, Indicates temperature measurement point The approximate temperature gradient at the point is given. A larger value indicates a steeper temperature change around the measuring point, suggesting a higher likelihood of localized abnormal heating or heat dissipation obstruction. The larger the value, the stronger the amplification effect of aging on the temperature measuring point; conversely, if the temperature difference between adjacent points is small, then... The value is close to 1, and the aging contribution is calculated based on the actual temperature without additional amplification. For the first or last temperature measurement point, use itself and the next or previous temperature measurement point for calculation. In this case, the interval distance does not need to be multiplied by 2 during the calculation.

[0058] like Figure 4 As shown, the gradient factor increases significantly in areas with drastic temperature changes, such as large temperature differences between adjacent temperature measurement points, while it remains at a low level in areas with gentle temperature distribution, effectively highlighting high-risk locations with local temperature anomalies.

[0059] Specifically, the gradient sensitivity coefficient is preset based on the mechanical strength test data of the insulation materials used in the transformer; for brittle materials in the insulation, the value of the gradient sensitivity coefficient is greater than that for tough materials. For example, for cellulose, which is in the later stages of aging and has a brittle texture, a larger value can be used. Value, such as For new materials with good toughness, a smaller [size / size] can be used. Value, such as .

[0060] Specifically, the gradient factor is used to amplify the aging assessment of areas with local temperature anomalies.

[0061] S4: Determine the cumulative equivalent aging time of each temperature measurement point within the current evaluation period.

[0062] It should be noted that the lifespan of the insulation materials used in transformers is a long-term cumulative process, not determined solely by the temperature at a single moment. For example, a transformer may experience short periods of high temperature (e.g., 80°C) during peak summer loads, and moderate temperatures (e.g., 50°C) during light nighttime loads. The impact of these two conditions on aging needs to be calculated separately and then accumulated. Therefore, this step accumulates the aging rate (the product of the rate factor and the gradient amplification factor) at different times through time integration, obtaining the total aging time equivalent to that under ideal conditions, thereby quantifying the gradual depletion of insulation lifespan under long-term operating conditions.

[0063] Based on the velocity factor and gradient factor of each temperature measuring point at each moment within the evaluation period (such as a day, a week, or a month), the cumulative equivalent aging time of each temperature measuring point within the current evaluation period is determined.

[0064] Specifically, the cumulative equivalent aging time satisfies:

[0065] ;

[0066] In the formula, Temperature measurement point The cumulative equivalent aging time during the current assessment period Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. This represents the time micro-element of the current evaluation period.

[0067] in, This represents the actual aging rate at the target point at that moment, i.e., the multiple of the aging rate relative to the ideal temperature. A larger value indicates a faster insulation aging rate at that point at that moment. For example, if... (The aging rate is twice that of the ideal lifespan corresponding to the ideal state). (With a gradient amplification of 1.5 times), the actual aging rate is 3 / hour. This means that the aging consumption in this hour (time interval, which can be set according to specific implementation conditions) is equivalent to the consumption in 3 hours under ideal conditions. Therefore, the larger this value, the better. The larger the value, the greater the accumulated equivalent aging time; conversely, if at a certain moment... , If the aging rate is 0.5 / hour, then only 0.5 hours of equivalent aging time will be accumulated per hour. This represents the time element of the current evaluation period. The larger the value, the longer the duration of a single time segment in the integration calculation. Therefore, under the same aging rate, the time is longer. The larger the aging time, the greater the cumulative aging time; conversely, the smaller the aging time, the greater the cumulative aging time.

[0068] S5: Determine the remaining life of the transformer after the current assessment period.

[0069] It should be noted that the overall insulation life of a transformer is determined by its weakest point, and the aging risk varies significantly at different temperature measurement points: some areas may become "weak links" due to prolonged high temperatures or drastic temperature gradients, and their aging consumption has a greater impact on the overall lifespan. Therefore, this step assigns weights to each point based on the proportion of its maximum aging rate during the assessment period, weights and sums the cumulative equivalent aging time of each point, and then subtracts the total consumption from the nominal lifespan of the insulation material to obtain the remaining lifespan, thus achieving a dynamic assessment of the transformer's lifespan.

[0070] The remaining lifespan of the transformer after the previous assessment period is determined based on the transformer's remaining lifespan after the previous assessment period, the cumulative equivalent aging time, and the speed factor.

[0071] Specifically, the remaining life of the transformer after the current assessment period satisfies:

[0072] ;

[0073] In the formula, This represents the remaining lifespan of the transformer after the current assessment period. The remaining life of the transformer after the previous assessment period (when the life assessment is first conducted). The ideal lifespan of insulation materials used in transformers is typically [missing information]. Years can be converted into hours, such as 20 years ≈ 175,200 hours. In subsequent assessments, the remaining lifespan of the transformer after the previous assessment period will be updated to achieve dynamic tracking. The number of temperature measurement points, Temperature measurement point The cumulative equivalent aging time during the current assessment period.

[0074] Specifically, the aging weight satisfies:

[0075] ;

[0076] In the formula, Temperature measurement point Aging weights at all temperature measurement points Temperature measurement points used to characterize the transformer The maximum value of the rate factor of aging rate at all times within the current evaluation period. This represents the number of temperature measurement points.

[0077] in, Indicates temperature measurement point The proportion of the maximum aging rate during the current assessment period to the total maximum aging rates of all points. A larger value indicates that the highest aging rate experienced by this temperature measurement point during operation represents a higher percentage of the overall total (i.e., the area faced a more severe aging risk). The higher the proportion in total consumption, the lower the proportion; conversely, the lower the proportion, the higher the proportion in total consumption. Indicates temperature measurement point The equivalent aging time accumulated during the current assessment period. The larger this value, the more lifespan the insulation material at that temperature measurement point has consumed during long-term operation, and the greater the total lifespan consumption. The smaller the remaining lifespan, the greater the remaining lifespan; conversely, the greater the remaining lifespan ....

[0078] Thus, by integrating the temperature distribution throughout the space, the dynamic aging rate, and the local risk weight, this invention completes the assessment of the remaining life of the transformer, providing a scientific basis for subsequent equipment operation and maintenance decisions (such as load adjustment and maintenance plan formulation).

[0079] This invention also discloses a transformer life assessment system, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a transformer life assessment method according to the present invention.

[0080] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0081] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for assessing the lifespan of a transformer, characterized in that, include: Obtain the temperature values ​​at various times during the current evaluation period from multiple temperature measurement points that are equidistantly arranged along the transformer windings. For each moment in the current evaluation period, based on the apparent activation energy, gas constant, temperature value corresponding to the ideal life of the transformer, and temperature value of each temperature measuring point at that moment, determine the rate factor used to characterize the aging rate of each temperature measuring point of the transformer at that moment. Based on the temperature difference between the temperature measurement points before and after each temperature measurement point at that moment, and the distance between the temperature measurement points before and after each temperature measurement point, a gradient factor is determined to characterize the degree of temperature change in the region to which each temperature measurement point belongs at that moment. Based on the velocity factor and gradient factor of each temperature measuring point at each moment during the evaluation period, determine the cumulative equivalent aging time of each temperature measuring point during the current evaluation period, satisfying the following: ； Temperature measurement point The cumulative equivalent aging time during the current assessment period Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. This represents the time micro-element of the current evaluation period; The remaining lifespan of the transformer after the previous assessment period is determined based on the transformer's remaining lifespan after the previous assessment period, the cumulative equivalent aging time, and the speed factor, including: For each temperature measurement point, the aging weight of that temperature measurement point among all temperature measurement points is determined based on the speed factor; The sum of the products of the cumulative equivalent aging time of each temperature measurement point and the corresponding aging weight is taken as the total equivalent aging consumption time of the transformer in the current evaluation period. Subtract the remaining life of the transformer after the previous assessment period from the total equivalent aging time to obtain the remaining life of the transformer after the current assessment period. Aging weights are satisfied: ； Temperature measurement point Aging weights at all temperature measurement points Temperature measurement points used to characterize the transformer The maximum value of the rate factor of aging rate at all times within the current evaluation period. This represents the number of temperature measurement points.

2. The transformer life assessment method according to claim 1, characterized in that, The temperature value is the temperature value after filtering and noise reduction.

3. The transformer life assessment method according to claim 1, characterized in that, The velocity factor satisfies: ； In the formula, Temperature measurement points used to characterize the transformer At any moment The rate factor of aging rate The apparent activation energy of the insulating material used in transformers. The gas constant is... This refers to the temperature value corresponding to the ideal lifespan of the transformer. Temperature measurement point At any moment Temperature value, It is a natural exponential function.

4. The transformer life assessment method according to claim 1, characterized in that, The gradient factor satisfies: ； In the formula, For characterizing temperature measurement points The region at time Gradient factor for the degree of drastic temperature change. The preset gradient sensitivity coefficient, and These are the temperature measurement points. The temperature measurement points that are adjacent to each other at time Temperature value, The distance between two adjacent temperature measuring points. The maximum and minimum value normalization function, It is the absolute value symbol.

5. The transformer life assessment method according to claim 4, characterized in that, The gradient sensitivity coefficient is preset based on the mechanical strength test data of the insulating materials used in the transformer; for brittle materials in the insulating material, the value of the gradient sensitivity coefficient is greater than that for tough materials in the insulating material.

6. A method for assessing the lifespan of a transformer according to claim 1 or 4, characterized in that, The gradient factor is used to amplify the aging assessment of areas with localized temperature anomalies.

7. A transformer life assessment system, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement a transformer life assessment method according to any one of claims 1-6.

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