Distribution transformer energy efficiency determination test method and device
By establishing a battery-powered and composite loss model, the problem of nonlinear factors affecting transformer energy efficiency assessment was solved, and a continuous energy efficiency curve was generated, enabling accurate and convenient assessment of transformer energy efficiency and reducing equipment and site requirements.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 郑州市金中电气有限公司
- Filing Date
- 2026-01-28
- Publication Date
- 2026-04-28
AI Technical Summary
Existing technologies, when evaluating transformer energy efficiency, ignore nonlinear factors such as harmonics and stray losses, resulting in calculation results that do not match actual operating conditions. This makes it impossible to accurately select high-efficiency transformers, and the technology relies on large power grid equipment, which is expensive and cumbersome to operate.
Using batteries as the test power source, a composite loss model separating iron loss and copper loss is established. By adjusting the test load and battery power supply status, data is collected and the model coefficients are corrected to generate a continuous energy efficiency curve. The curvature is used to determine the key judgment points, thereby achieving a more comprehensive energy efficiency assessment.
It enables convenient on-site testing of transformer energy efficiency, generates continuous energy efficiency curves, accurately identifies loss characteristics, improves the accuracy and comprehensiveness of energy efficiency assessment, and reduces dependence on equipment and site.
Smart Images
Figure CN121933985A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of transformer testing, and in particular relates to a method and apparatus for determining the energy efficiency of distribution transformers. Background Technology
[0002] Commonly used energy efficiency testing methods are based on traditional open-circuit and short-circuit tests. Open-circuit tests measure the no-load loss of a transformer at rated voltage, while short-circuit tests measure the load loss at rated current. The transformer's operating efficiency at different load rates is calculated by superimposing these two losses measured under specific operating conditions. Traditional methods heavily rely on high-capacity, high-stability AC test power supplies, making energy efficiency testing difficult at production sites, user sites, or in situations lacking specialized testing facilities. The equipment requirements are high, and the costs are expensive. The testing process is cumbersome and time-consuming, especially when testing large transformers, where the energy consumption itself is considerable. Furthermore, the efficiency of a transformer is typically assessed based on several discrete load rate points selected according to relevant energy efficiency standards. This discrete-point-based approach cannot continuously evaluate the transformer's energy efficiency characteristics across the entire load range. The change in transformer efficiency with load rate is a non-linear curve, and the peak efficiency point and the region of drastic efficiency change vary from transformer to transformer. If the lowest point or key change point of the efficiency curve falls precisely between two standard assessment points, the discrete detection method may miss the worst-case operating condition, leading to an overly optimistic assessment of transformer energy efficiency or even misjudgment. This could result in some products with poor energy efficiency performance in specific load ranges being incorrectly rated as qualified, hindering the screening of transformer energy efficiency levels and impeding the promotion and application of high-quality, high-efficiency power equipment. Therefore, developing a new energy efficiency assessment method that is independent of the large power grid, uses more accurate models, and provides more comprehensive judgments is a pressing issue in the current technological field. Summary of the Invention
[0003] This invention proposes a test method for determining the energy efficiency of distribution transformers, which addresses the problem that existing technologies neglect the influence of nonlinear factors such as harmonics and stray losses, potentially leading to discrepancies between calculated energy efficiency and actual operating conditions, thus failing to effectively screen transformer energy efficiency levels. The method includes the following steps: Connect the battery to the primary side of the transformer under test and connect the first test load to the secondary side. Simultaneously collect the input voltage, input current and output power sequence of the first time period. Establish a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and use the data of the first time period to solve for the initial model coefficients. Based on the initial model coefficients, the contribution ratio of iron loss to copper loss under the first time period is calculated, and the test load or battery power supply state is adjusted accordingly to collect data for the second time period. Based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients, the initial model coefficients are corrected to obtain updated model coefficients; the rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, thereby generating a continuous energy efficiency curve representing the efficiency change with load rate under rated voltage. The curvature of the energy efficiency curve within a preset load rate range is calculated, and multiple judgment points are determined by non-uniform sampling on the curve based on the absolute value of the curvature, so that the sampling density in the region with larger curvature is higher; the energy efficiency of the transformer is judged based on whether the efficiency values of all judgment points meet the preset standard energy efficiency level requirements.
[0004] Optionally, the step of establishing a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and solving for the initial model coefficients using the data from the first time period, includes: Establish total loss With input voltage Input current The functional relationship is ,in This is the iron loss coefficient. Copper loss coefficient; Substituting each set of input voltage and current collected in the first time period, along with the calculated total loss, into the functional relationship, and using the least squares method for fitting, the iron loss coefficient is obtained. Copper loss coefficient The initial value.
[0005] Optionally, the step of calculating the contribution ratio of iron loss to copper loss under the first time period operating condition based on the initial model coefficients, and adjusting the test load or battery power supply state accordingly to collect data for the second time period, includes: Using the initial model coefficients and the average input voltage of the first time period Average input current Calculate the average iron loss With average copper loss ; like If the battery supply voltage is reduced by 15%, the test load impedance will be reduced to increase the input current by 20%. like If the battery supply voltage is increased by 15%, the test load impedance will be increased to reduce the input current by 20%. like If the battery supply voltage remains constant, the test load impedance is adjusted to obtain an input current value different from that in the first time period.
[0006] Optionally, the step of correcting the initial model coefficients based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients to obtain updated model coefficients includes: All data points collected in the first and second time periods are combined to form an extended dataset. For the extended dataset, the composite loss model is refitted using the weighted least squares method to obtain the updated model coefficients.
[0007] Optionally, the step of substituting the rated voltage into the composite loss model determined by the updated model coefficients to calculate the loss values under different load rates, and then generating a continuous energy efficiency curve representing the efficiency change with load rate under the rated voltage, includes: According to the updated iron loss coefficient and the rated voltage of the transformer under test Calculate the rated iron loss ; According to the updated copper loss coefficient and the rated input current of the transformer under test Calculate the rated copper loss ; Set load rate From 10% to 120%; For each load rate Calculate the corresponding output power and total loss ,in This refers to the rated output power of the transformer. According to the formula Calculate the efficiency at the current load rate, connect all calculation points, and form a continuous energy efficiency curve.
[0008] Optionally, the step of calculating the curvature of the energy efficiency curve within a preset load rate range, and determining multiple judgment points by non-uniformly sampling points on the curve based on the absolute value of the curvature, includes: Within a load range of 20% to 100%, according to the energy efficiency curve function Calculate curvature: Calculate the absolute value of the average curvature within the range. The curvature threshold is a preset multiple of the absolute value of the average curvature; In curvature For regions with load rates below the threshold, a judgment point is taken every 15% of the load rate. In curvature For regions with a load rate greater than or equal to the threshold, a decision point is taken every 5% of the load rate, and points corresponding to 50% and 100% load rates are forcibly included as decision points.
[0009] Optionally, the step of determining the energy efficiency of the transformer based on whether the efficiency values at all determination points meet the preset standard energy efficiency level requirements includes: Load the standard efficiency table corresponding to the target energy efficiency level, which specifies the minimum efficiency limit at a specific load rate; For each decision point, obtain the load rate of that decision point. and efficiency value ; By using table lookup and linear interpolation methods, the load factor is obtained. Standard minimum efficiency limit ; Compare and If all decision points satisfy If the condition is met at any point, the transformer is deemed to meet the energy efficiency rating. If any condition is not met at any point, the transformer is deemed not to meet the rating.
[0010] Furthermore, the present invention also relates to a testing device for determining the energy efficiency of a distribution transformer, comprising the following modules: A module is established to connect the battery to the primary side of the transformer under test and the first test load to the secondary side, and to synchronously collect the input voltage, input current and output power sequence of the first time period; a composite loss model is established to decompose the total loss into iron loss related to the input voltage and copper loss related to the input current, and the initial model coefficients are obtained by solving the data of the first time period. The calculation module is used to calculate the contribution ratio of iron loss to copper loss under the first time period operating conditions based on the initial model coefficients, and adjust the test load or battery power supply state accordingly to collect data for the second time period. The generation module is used to correct the initial model coefficients based on the deviation between the measured loss and the loss predicted by the initial model coefficients in the second time period, and obtain the updated model coefficients; the rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, and then a continuous energy efficiency curve representing the efficiency change with the load rate under the rated voltage is generated. The determination module is used to calculate the curvature of the energy efficiency curve within a preset load rate range, and to perform non-uniform sampling on the curve according to the absolute value of the curvature to determine multiple determination points, so that the sampling density in the area with larger curvature is higher; and to determine the energy efficiency of the transformer based on whether the efficiency values of all determination points meet the preset standard energy efficiency level requirements.
[0011] Preferably, the step of establishing a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and solving for the initial model coefficients using the data from the first time period, includes: Establish total loss With input voltage Input current The functional relationship is ,in This is the iron loss coefficient. Copper loss coefficient; Substituting each set of input voltage and current collected in the first time period, along with the calculated total loss, into the functional relationship, and using the least squares method for fitting, the iron loss coefficient is obtained. Copper loss coefficient The initial value.
[0012] Preferably, the step of calculating the contribution ratio of iron loss to copper loss under the first time period operating condition based on the initial model coefficients, and adjusting the test load or battery power supply state accordingly to collect data for the second time period, includes: Using the initial model coefficients and the average input voltage of the first time period Average input current Calculate the average iron loss With average copper loss ; like If the battery supply voltage is reduced by 15%, the test load impedance will be reduced to increase the input current by 20%. like If the battery supply voltage is increased by 15%, the test load impedance will be increased to reduce the input current by 20%. like If the battery supply voltage remains constant, the test load impedance is adjusted to obtain an input current value different from that in the first time period.
[0013] Preferably, the step of correcting the initial model coefficients based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients to obtain updated model coefficients includes: All data points collected in the first and second time periods are combined to form an extended dataset. For the extended dataset, the composite loss model is refitted using the weighted least squares method to obtain the updated model coefficients.
[0014] Preferably, the step of substituting the rated voltage into the composite loss model determined by the updated model coefficients to calculate the loss values under different load rates, and then generating a continuous energy efficiency curve representing the efficiency change with load rate under the rated voltage, includes: According to the updated iron loss coefficient and the rated voltage of the transformer under test Calculate the rated iron loss ; According to the updated copper loss coefficient and the rated input current of the transformer under test Calculate the rated copper loss ; Set load rate From 10% to 120%; For each load rate Calculate the corresponding output power and total loss ,in This refers to the rated output power of the transformer. According to the formula Calculate the efficiency at the current load rate, connect all calculation points, and form a continuous energy efficiency curve.
[0015] Preferably, the step of calculating the curvature of the energy efficiency curve within a preset load rate range, and determining multiple judgment points by non-uniformly sampling points on the curve based on the absolute value of the curvature, includes: Within a load range of 20% to 100%, according to the energy efficiency curve function Calculate curvature: Calculate the absolute value of the average curvature within the range. The curvature threshold is a preset multiple of the absolute value of the average curvature; In curvature For regions with load rates below the threshold, a judgment point is taken every 15% of the load rate. In curvature For regions with a load rate greater than or equal to the threshold, a decision point is taken every 5% of the load rate, and points corresponding to 50% and 100% load rates are forcibly included as decision points.
[0016] Preferably, the step of determining the energy efficiency of the transformer based on whether the efficiency values at all determination points meet the preset standard energy efficiency level requirements includes: Load the standard efficiency table corresponding to the target energy efficiency level, which specifies the minimum efficiency limit at a specific load rate; For each decision point, obtain the load rate of that decision point. and efficiency value ; By using table lookup and linear interpolation methods, the load factor is obtained. Standard minimum efficiency limit ; Compare and If all decision points satisfy If the condition is met at any point, the transformer is deemed to meet the energy efficiency rating. If any condition is not met at any point, the transformer is deemed not to meet the rating.
[0017] This invention uses batteries as the test power source, reducing the requirements for testing sites and equipment, and eliminating dependence on the power grid, making on-site and convenient testing of transformer energy efficiency possible. By establishing a composite loss model that separates iron losses and copper losses, and using measured data under different operating conditions to correct the model, the true loss characteristics of the transformer can be identified more accurately, thereby generating a complete continuous energy efficiency curve. This curve not only reflects the transformer's performance at all load rates, but also uses the curve curvature to determine key judgment points, focusing the assessment on the region with the most drastic efficiency changes, thus making a more comprehensive and reliable judgment on the transformer's energy efficiency. Attached Figure Description
[0018] Figure 1 A flowchart of the first embodiment; Figure 2 This is a connection diagram of a transformer energy efficiency testing system; Figure 3 This is a schematic diagram of operating condition adjustments based on loss characteristics; Figure 4 This is a schematic diagram of the generated transformer energy efficiency curve; Figure 5 This is a schematic diagram illustrating the selection of non-uniformity determination points based on curvature. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0020] In the first embodiment, the present invention proposes a test method for determining the energy efficiency of a distribution transformer, such as... Figure 1 This includes the following steps: S1, connect the battery to the primary side of the transformer under test and connect the first test load to the secondary side, and synchronously collect the input voltage, input current and output power sequence of the first time period; establish a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and use the data of the first time period to solve for the initial model coefficients; Specifically, the battery is connected to the primary winding of a transformer via a controllable inverter capable of generating alternating current at a specified voltage and frequency. An adjustable electronic load or resistance box is connected to the secondary winding of the transformer as the first test load, such as... Figure 2 A multi-channel power analyzer is used, with the analyzer's voltage probe and current clamp connected to the primary and secondary sides of the transformer, respectively. A sampling frequency is set, for example, 100 data points are collected per second, and the sampling is continued for tens of seconds to obtain a series of time-ordered instantaneous input voltage values, instantaneous input current values, and active power values output from the secondary side.
[0021] Establish a total loss model for Iron loss Modeled as with input voltage The relevant functions are in the form of copper loss Modeled as input current The relevant functions are in the form of , and These are the model coefficients to be determined. For each set of synchronized data points collected in the first time period, calculate the total loss at that moment. A series of information were obtained. and The system of equations was then used. The least squares method was employed to fit this overdetermined system of equations, and the coefficients that minimize the sum of squared errors between the model-predicted loss and the measured loss for all data points were obtained. and , which are the initial model coefficients.
[0022] In an optional embodiment, the step of establishing a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and solving for the initial model coefficients using the data from the first time period, includes: Establish total loss With input voltage Input current The functional relationship is ,in This is the iron loss coefficient. Copper loss coefficient; Substituting each set of input voltage and current collected in the first time period, along with the calculated total loss, into the functional relationship, and using the least squares method for fitting, the iron loss coefficient is obtained. Copper loss coefficient The initial value.
[0023] Collect operational data for the first time period, such as recording the input voltage at one hundred time points. Input current Input power and output power For each time point, the total loss It is calculated by subtracting the output power from the input power. For example, at one moment, the input voltage is measured to be 48V, the input current is 2A, and the total loss is 5.5W; at another moment, the input voltage is 48.1V, the input current is 2.5A, and the total loss is 7.2W.
[0024] Establish a composite loss model and solve for the coefficients. Iron loss is mainly caused by hysteresis and eddy current effects in the magnetic core and is proportional to the square of the magnetic flux density, which in turn is approximately proportional to the input voltage. The iron loss, represented by the Joule heat generated when current flows through the winding resistance, is proportional to the square of the input current. Substituting one hundred data points into the equations yields an overdetermined system of equations. The least squares method is then used to find the optimal iron loss coefficient. Copper loss coefficient This minimizes the sum of squared errors between the model-predicted loss and the measured loss. For example, the initial iron loss coefficient can be obtained through fitting calculations. The initial copper loss coefficient is 0.0015. It is 0.5.
[0025] S2, Based on the initial model coefficients, calculate the contribution ratio of iron loss to copper loss under the first time period operating conditions, and adjust the test load or battery power supply state accordingly to collect data for the second time period; Using the obtained initial model coefficients and The average iron loss under this operating condition is calculated by taking the average value of the input voltage and current data collected in the first time period, as well as the average value of the input voltage and current data collected in the first time period. With average copper loss Calculate the ratio of the two. To make the model more universal, it is necessary to collect data with significant differences in loss composition. If R is much greater than 1, it indicates that iron loss is dominant. In this case, the test load on the secondary side should be increased to raise the input current and thus increase the proportion of copper loss. If R is much less than 1, the test load should be reduced. After adjusting the load, the data acquisition process in the first step is repeated to obtain the data sequence for the second time period.
[0026] In an optional embodiment, the step of calculating the contribution ratio of iron loss to copper loss under the first time period operating condition based on the initial model coefficients, and adjusting the test load or battery power supply state accordingly to collect data for the second time period, includes: Using the initial model coefficients and the average input voltage of the first time period Average input current Calculate the average iron loss With average copper loss ; like If the battery supply voltage is reduced by 15%, the test load impedance will be reduced to increase the input current by 20%. like If the battery supply voltage is increased by 15%, the test load impedance will be increased to reduce the input current by 20%. like If the battery supply voltage remains constant, the test load impedance is adjusted to obtain an input current value different from that in the first time period.
[0027] The loss composition is evaluated using the initial model coefficients obtained in the previous stage and the average operating data of the first time period. Assuming the average input voltage is obtained by calculating the average of one hundred data points in the first time period... 48V, average input current The initial coefficient is 2A. Using the initial coefficients obtained above... and Calculate the average iron loss =3.456W, and average copper loss =2W.
[0028] The ratio of average iron loss to average copper loss is calculated to be 1.728. This ratio, falling between one-fifth and five, indicates that the contributions of iron loss and copper loss are relatively balanced under the first time period's operating conditions. According to the preset adjustment strategy, the battery supply voltage should be kept constant at 48V, but the test load needs to be adjusted to collect data under different operating conditions. For example, by reducing the load impedance, the target value of the input current can be set to 3A, which is higher than the average current in the first time period, thereby obtaining more information about the copper loss characteristics in the data acquisition of the second time period.
[0029] In contrast, if the calculated ratio of iron loss to copper loss is greater than five, for example, iron loss is 10W and copper loss is 1W, it indicates that the data reflects the characteristics of iron loss. In this case, reducing the supply voltage by 15% to 40.8V reduces iron loss, while simultaneously increasing the input current by 20% to 2.4A enhances the impact of copper loss, thus allowing the second data acquisition to more reliably correct the copper loss coefficient. These adjustments ensure that the model obtains sufficient training data in different loss-dominant regions, improving the model's accuracy.
[0030] S3. Based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients, the initial model coefficients are corrected to obtain updated model coefficients. The rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, thereby generating a continuous energy efficiency curve representing the change of efficiency with load rate under rated voltage. Specifically, all datasets collected in the first and second time periods are merged into a larger dataset. The least squares method is then applied to resolve the coefficients in the composite loss model for the expanded dataset, which includes two different operating conditions. and Because the new dataset covers a wider operating range and different loss configurations, the new set of coefficients obtained through global fitting... and Compared to the initial model coefficients, the updated model coefficients more accurately reflect the loss characteristics of the transformer under various operating conditions.
[0031] Obtain the rated voltage from the nameplate of the transformer under test. and rated capacity At this point, the loss model of the transformer operating at rated voltage becomes... Where β is the load factor, The input current at the corresponding load factor β can be approximated as β multiplied by the rated current. The output power of the transformer ,in This is the rated power factor. Therefore, the efficiency at any load factor β is... By allowing the load factor β to vary continuously within a range, for example from 0.05 to 1.2, in steps of 0.001, the efficiency η value corresponding to each β is calculated. Connecting these points yields a smooth and continuous energy efficiency curve.
[0032] In an optional embodiment, the step of correcting the initial model coefficients based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients to obtain updated model coefficients includes: All data points collected in the first and second time periods are combined to form an extended dataset. For the extended dataset, the composite loss model is refitted using the weighted least squares method to obtain the updated model coefficients.
[0033] The 100 data points collected in the first time period were combined with another 100 data points collected in the second time period under adjusted operating conditions. This resulted in an expanded dataset containing 200 data points, covering a wider range of operating voltages and currents.
[0034] use The model structure is as follows. However, during the second fitting, different weights are assigned to data points from different sources. Specifically, the original one hundred data points from the first time period are assigned a weight of 1.0. For the one hundred new data points from the second time period, collected under specific adjusted conditions, a higher weight value, such as 1.5, is assigned.
[0035] By employing the aforementioned weighting method, the optimization algorithm prioritizes data points from the second time period when minimizing the sum of squared errors. This is to allow the model to preferentially correct data points with significant prediction errors from the initial model, specifically collected through adjustments to the operating conditions, thereby reliably improving the overall prediction accuracy of the model. Solving the weighted least squares problem yields a set of updated model coefficients, such as the iron loss coefficient. The copper loss coefficient was adjusted from 0.0015 to 0.00148. The value was revised from 0.5 to 0.512. This updated set of coefficients more accurately represents the loss characteristics of the transformer throughout its operating range, such as... Figure 3 .
[0036] In an optional embodiment, the step of substituting the rated voltage into the composite loss model determined by the updated model coefficients to calculate the loss values under different load rates, and then generating a continuous energy efficiency curve representing the efficiency change with load rate under the rated voltage, includes: According to the updated iron loss coefficient and the rated voltage of the transformer under test Calculate the rated iron loss ; According to the updated copper loss coefficient and the rated input current of the transformer under test Calculate the rated copper loss ; Set load rate From 10% to 120%; For each load rate Calculate the corresponding output power and total loss ,in This refers to the rated output power of the transformer. According to the formula Calculate the efficiency at the current load rate, connect all calculation points, and form a continuous energy efficiency curve.
[0037] Assume the rated voltage of the transformer under test 48V, rated input current It is 5A, rated output power It is 230W. Using the updated coefficients. and Calculate the iron loss under rated voltage. W, this value is considered a fixed loss under rated voltage. Simultaneously, the rated copper loss under full load is calculated. W, where the value is a variable loss reference corresponding to the full-load current.
[0038] Set a loop to adjust the load rate. Starting with 0.1 (10% load), the load increments by 0.01 (1%), increasing to 1.2 (120% load). At each step of the loop, the output power, total losses, and efficiency at the current load rate are calculated. For example, when the load rate... When the value is 0.5 (50%), the output power is W. The total loss at this point consists of fixed iron loss and copper loss that varies with the square of the load factor, i.e. W.
[0039] Calculate the efficiency value at this point according to the efficiency definition formula. The result is approximately 94.56%. The calculation process generates an efficiency value for each percentage point between 10% and 120% load rate. Connecting all the calculated efficiency points in order of load rate forms a smooth and continuous efficiency curve, which fully represents the transformer's efficiency performance from light load to overload at rated voltage. Figure 4 .
[0040] S4. Calculate the curvature of the energy efficiency curve within the preset load rate range, and perform non-uniform sampling on the curve according to the absolute value of the curvature to determine multiple judgment points, so that the sampling density in the area with larger curvature is higher; judge the energy efficiency of the transformer according to whether the efficiency values of all judgment points meet the preset standard energy efficiency level requirements.
[0041] Specifically, take the first derivative of the function η(β) with respect to β. and second derivative In one embodiment, according to the curvature formula Calculate the curvature at each point on the energy efficiency curve. Set a total number of judgment points, for example, 50. Divide the preset load rate range, such as 20% to 100%, into several small intervals. Calculate the average curvature within each small interval, and then proportionally allocate the 50 judgment points to each small interval based on the magnitude of the average curvature, allocating more points to intervals with larger curvature and fewer points to intervals with smaller curvature. Consult relevant energy efficiency standard documents to obtain the minimum efficiency requirements for the target energy efficiency level at different load rates. Compare the efficiency value corresponding to each judgment point with the efficiency requirements for the corresponding load rate in the standard. If the efficiency values of all judgment points are higher than or equal to the standard requirements, the transformer is judged to meet the energy efficiency level; otherwise, it is judged to not meet the requirements.
[0042] More specifically, the calculation of the curvature of the energy efficiency curve within a preset load rate range, and the determination of multiple judgment points by non-uniformly sampling points on the curve based on the absolute value of the curvature, includes: Within a load range of 20% to 100%, according to the energy efficiency curve function Calculate curvature: Calculate the absolute value of the average curvature within the range. The curvature threshold is a preset multiple of the absolute value of the average curvature; In curvature For regions with load rates below the threshold, a judgment point is taken every 15% of the load rate. In curvature For regions with a load rate greater than or equal to the threshold, a decision point is taken every 5% of the load rate, and points corresponding to 50% and 100% load rates are forcibly included as decision points.
[0043] Based on the load rate range of 20% to 100%, for this function... The continuous energy efficiency curve needs to have its first derivative calculated. and second derivative The derivative can be obtained analytically by differentiating the efficiency formula or using numerical difference methods. Substituting the derivative value into the curvature formula yields the curvature at each point within the 20% to 100% load rate range. Typically, the efficiency curve is relatively flat with a smaller curvature near the peak efficiency point, while it changes more rapidly and has a larger curvature in the light and heavy load regions.
[0044] Calculate the average of the absolute values of curvature at all points within the entire interval. Set the curvature threshold to For example, if the absolute value of the average curvature is 0.8, then the curvature threshold is set to 1.2. Judgment points are selected on the energy efficiency curve based on this threshold. In regions where the absolute value of curvature is less than 1.2, representing a gentle curve shape change, a sparser sampling strategy is adopted, selecting a point every 15% of the load rate. For example, if the curvature in the 40% to 70% load rate range is all less than 1.2, perhaps only the 40%, 55%, and 73% points are selected.
[0045] In regions where the absolute value of curvature is greater than or equal to 1.2, the curve is severely curved, and efficiency changes rapidly, requiring denser sampling. A point is selected every 5% of the load rate. For example, if the curvature is large in the 20% to 35% and 80% to 100% ranges, points are taken at 5% intervals within these regions. Furthermore, regardless of the curvature, the 50% and 100% load rate points, which are considered industry-standard, are forcibly selected as decision points. This non-uniform sampling method detects key features of the energy efficiency curve with a minimal number of decision points, such as… Figure 5 .
[0046] In an optional embodiment, the step of determining the energy efficiency of the transformer based on whether the efficiency values at all determination points meet the preset standard energy efficiency level requirements includes: Load the standard efficiency table corresponding to the target energy efficiency level, where the efficiency table specifies the minimum efficiency limit at a specific load rate; For each determination point, obtain the load rate of the determination point and the efficiency value ; Through the method of looking up the table and linear interpolation, obtain the standard minimum efficiency limit value at the load rate ; ; Compare with . If all determination points satisfy , it is determined that the transformer meets the energy efficiency level. If there is any determination point that does not meet the condition, it is determined as not meeting.
[0047] Load the standard efficiency requirement table corresponding to a target energy efficiency level, such as the first-level energy efficiency. This table usually does not cover all load rates, but defines the minimum efficiency requirements at several key load points. For example, it is stipulated that the efficiency is not less than 93% at 25% load, not less than 95% at 50% load, not less than 94.5% at 75% load, and not less than 94% at 100% load. At the same time, have the above-mentioned set of determination points with non-uniform distribution, such as including six load rate points of 20%, 30%, 50%, 80%, 95% and 100% and the corresponding measured efficiency values.
[0048] For those determination points whose load rates are exactly defined in the standard table, such as 50% and 100%, directly read the standard limit values. For determination points whose load rates are not directly listed in the standard table, such as 30%, linear interpolation needs to be used to calculate the standard limit values. For example, to determine the standard at 30% load, find two adjacent points in the standard table, namely 25% and 50%, and perform linear interpolation between the standard efficiency values of these two points to obtain the minimum efficiency requirement at 30% load rate.
[0049] Compare the measured efficiency value of each determination point with the corresponding standard efficiency limit value. For example, at the 50% load rate point, compare the measured efficiency, such as 95.2%, with the standard requirement of 95%. Since the measured value is higher, this point is qualified. The comparison process is carried out sequentially for all six determination points. Only when the measured efficiency values of all six determination points are greater than or equal to their respective standard limit values can it be determined that the transformer meets the first-level energy efficiency standard. As long as the efficiency of any one determination point fails to meet the standard, it is determined that the transformer does not meet this energy efficiency level.
[0050] In the second embodiment, the present invention also provides a distribution transformer energy efficiency determination and testing device, including the following modules: A module is established to connect the battery to the primary side of the transformer under test and the first test load to the secondary side, and to synchronously collect the input voltage, input current and output power sequence of the first time period; a composite loss model is established to decompose the total loss into iron loss related to the input voltage and copper loss related to the input current, and the initial model coefficients are obtained by solving the data of the first time period. The calculation module is used to calculate the contribution ratio of iron loss to copper loss under the first time period operating conditions based on the initial model coefficients, and adjust the test load or battery power supply state accordingly to collect data for the second time period. The generation module is used to correct the initial model coefficients based on the deviation between the measured loss and the loss predicted by the initial model coefficients in the second time period, and obtain the updated model coefficients; the rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, and then a continuous energy efficiency curve representing the efficiency change with the load rate under the rated voltage is generated. The determination module is used to calculate the curvature of the energy efficiency curve within a preset load rate range, and to perform non-uniform sampling on the curve according to the absolute value of the curvature to determine multiple determination points, so that the sampling density in the area with larger curvature is higher; and to determine the energy efficiency of the transformer based on whether the efficiency values of all determination points meet the preset standard energy efficiency level requirements.
[0051] In this specification, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise limited, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. In this document, "a," "an," "the," "the," and "its" may also include plural forms unless the context clearly indicates otherwise. "Multiple" refers to at least two, such as 2, 3, 5, or 8, etc. "And / or" includes any and all combinations of the associated listed items.
[0052] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.
[0053] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for determining the energy efficiency of a distribution transformer, characterized in that, Includes the following steps: Connect the battery to the primary side of the transformer under test and connect the first test load to the secondary side. Simultaneously collect the input voltage, input current and output power sequence of the first time period. Establish a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and use the data of the first time period to solve for the initial model coefficients. Based on the initial model coefficients, the contribution ratio of iron loss to copper loss under the first time period is calculated, and the test load or battery power supply state is adjusted accordingly to collect data for the second time period. Based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients, the initial model coefficients are corrected to obtain updated model coefficients; the rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, thereby generating a continuous energy efficiency curve representing the efficiency change with load rate under rated voltage. The curvature of the energy efficiency curve within a preset load rate range is calculated, and multiple judgment points are determined by non-uniform sampling on the curve based on the absolute value of the curvature, so that the sampling density in the region with larger curvature is higher; the energy efficiency of the transformer is judged based on whether the efficiency values of all judgment points meet the preset standard energy efficiency level requirements.
2. The method according to claim 1, characterized in that, The establishment of a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and the calculation of initial model coefficients using the data from the first time period, includes: Establish total loss With input voltage Input current The functional relationship is ,in This is the iron loss coefficient. Copper loss coefficient; Substituting each set of input voltage and current collected in the first time period, along with the calculated total loss, into the functional relationship, and using the least squares method for fitting, the iron loss coefficient is obtained. Copper loss coefficient The initial value.
3. The method according to claim 2, characterized in that, Based on the initial model coefficients, the contribution ratio of iron loss to copper loss under the first time period operating conditions is calculated, and the test load or battery power supply state is adjusted accordingly to collect data for the second time period, including: Using the initial model coefficients and the average input voltage of the first time period Average input current Calculate the average iron loss With average copper loss ; like If the battery supply voltage is reduced by 15%, the test load impedance will be reduced to increase the input current by 20%. like If the battery supply voltage is increased by 15%, the test load impedance will be increased to reduce the input current by 20%. like If the battery supply voltage remains constant, the test load impedance is adjusted to obtain an input current value different from that in the first time period.
4. The method according to claim 1, characterized in that, The step of correcting the initial model coefficients based on the deviation between the measured loss during the second time period and the loss predicted by the initial model coefficients to obtain updated model coefficients includes: All data points collected in the first and second time periods are combined to form an extended dataset. For the extended dataset, the composite loss model is refitted using the weighted least squares method to obtain the updated model coefficients.
5. The method according to claim 1, characterized in that, The step of substituting the rated voltage into the composite loss model determined by the updated model coefficients to calculate the loss values under different load rates, and then generating a continuous energy efficiency curve representing the efficiency change with load rate under the rated voltage, includes: According to the updated iron loss coefficient and the rated voltage of the transformer under test Calculate the rated iron loss ; According to the updated copper loss coefficient and the rated input current of the transformer under test Calculate the rated copper loss ; Set load rate From 10% to 120%; For each load rate Calculate the corresponding output power and total loss ,in This refers to the rated output power of the transformer. According to the formula Calculate the efficiency at the current load rate, connect all calculation points, and form a continuous energy efficiency curve.
6. The method according to claim 1, characterized in that, The calculation of the curvature of the energy efficiency curve within a preset load rate range, and the determination of multiple judgment points by non-uniformly sampling points on the curve based on the absolute value of the curvature, includes: Within a load range of 20% to 100%, according to the energy efficiency curve function Calculate curvature: Calculate the absolute value of the average curvature within the range. The curvature threshold is a preset multiple of the absolute value of the average curvature; In curvature For regions with load rates below the threshold, a judgment point is taken every 15% of the load rate. In curvature For regions with a load rate greater than or equal to the threshold, a decision point is taken every 5% of the load rate, and points corresponding to 50% and 100% load rates are forcibly included as decision points.
7. The method according to claim 1, characterized in that, The step of determining the energy efficiency of the transformer based on whether the efficiency values at all determination points meet the preset standard energy efficiency level requirements includes: Load the standard efficiency table corresponding to the target energy efficiency level, which specifies the minimum efficiency limit at a specific load rate; For each decision point, obtain the load rate of that decision point. and efficiency value ; By using table lookup and linear interpolation methods, the load factor is obtained. Standard minimum efficiency limit ; Compare and If all decision points satisfy If the condition is met at any point, the transformer is deemed to meet the energy efficiency rating. If any condition is not met at any point, the transformer is deemed not to meet the rating.
8. A testing device for determining the energy efficiency of a distribution transformer, characterized in that, Includes the following modules: A module is established to connect the battery to the primary side of the transformer under test and the first test load to the secondary side, and to synchronously collect the input voltage, input current and output power sequence of the first time period; a composite loss model is established to decompose the total loss into iron loss related to the input voltage and copper loss related to the input current, and the initial model coefficients are obtained by solving the data of the first time period. The calculation module is used to calculate the contribution ratio of iron loss to copper loss under the first time period operating conditions based on the initial model coefficients, and adjust the test load or battery power supply state accordingly to collect data for the second time period. The generation module is used to correct the initial model coefficients based on the deviation between the measured loss and the loss predicted by the initial model coefficients in the second time period, and obtain the updated model coefficients; the rated voltage is substituted into the composite loss model determined by the updated model coefficients to calculate the loss value under different load rates, and then a continuous energy efficiency curve representing the efficiency change with the load rate under the rated voltage is generated. The determination module is used to calculate the curvature of the energy efficiency curve within a preset load rate range, and to perform non-uniform sampling on the curve according to the absolute value of the curvature to determine multiple determination points, so that the sampling density in the area with larger curvature is higher; and to determine the energy efficiency of the transformer based on whether the efficiency values of all determination points meet the preset standard energy efficiency level requirements.
9. The apparatus according to claim 8, characterized in that, The establishment of a composite loss model that decomposes the total loss into iron loss related to the input voltage and copper loss related to the input current, and the calculation of initial model coefficients using the data from the first time period, includes: Establish total loss With input voltage Input current The functional relationship is ,in This is the iron loss coefficient. Copper loss coefficient; Substituting each set of input voltage and current collected in the first time period, along with the calculated total loss, into the functional relationship, and using the least squares method for fitting, the iron loss coefficient is obtained. Copper loss coefficient The initial value.
10. The apparatus according to claim 8, characterized in that, Based on the initial model coefficients, the contribution ratio of iron loss to copper loss under the first time period operating conditions is calculated, and the test load or battery power supply state is adjusted accordingly to collect data for the second time period, including: Using the initial model coefficients and the average input voltage of the first time period Average input current Calculate the average iron loss With average copper loss ; like If the battery supply voltage is reduced by 15%, the test load impedance will be reduced to increase the input current by 20%. like If the battery supply voltage is increased by 15%, the test load impedance will be increased to reduce the input current by 20%. like If the battery supply voltage remains constant, the test load impedance is adjusted to obtain an input current value different from that in the first time period.