An energy efficiency evaluation method and system for current boosting tests of ultra-high voltage transformers.

Abstract

This invention belongs to the field of high-voltage power equipment testing and inspection technology, specifically relating to an energy efficiency evaluation method and system for ultra-high voltage transformer current-up tests. The method includes: acquiring the loop current, the output voltage on the power supply side, and the transformer oil temperature, and calculating the phase difference and real-time equivalent mode impedance; calculating the thermal drift factor and dynamic confidence weight of the current-up test loop based on the transformer oil temperature change rate and the fluctuation degree of the real-time equivalent mode impedance within the data observation window; calculating the basic energy efficiency value at the current sampling time based on the phase difference; and weighting the basic energy efficiency value at the current time and the energy efficiency evaluation index at the previous time based on the dynamic confidence weight to obtain the energy efficiency evaluation index at the current time. This invention improves upon the shortcomings of static calculation methods in dealing with real-time equivalent mode impedance drift and dynamic response lag by establishing a thermoelectric dynamic weighting logic.

Description

Technical Field

[0001] This invention relates to the field of high-voltage power equipment testing and inspection technology. More specifically, this invention relates to an energy efficiency evaluation method and system for current-boosting tests of ultra-high-voltage transformers. Background Technology

[0002] As a core hub of the State Grid, the stability of ultra-high voltage (UHV) transformers is crucial to the safe operation of the entire power system. During the factory acceptance or on-site commissioning testing of UHV transformers, the current-boosting test is an indispensable and critical step, primarily used to verify the transformer's long-term current-carrying capacity, the heat dissipation performance of the cooling system, and the correctness of the CT circuit wiring. Because UHV transformers have high inherent impedance, and the current required for the current-boosting test typically reaches thousands of amperes, directly using power frequency power for the current boosting would place extremely high demands on the power supply equipment's capacity, which is often difficult to meet in actual engineering sites. Therefore, construction and commissioning units typically utilize capacitor banks and transformer windings to form a series or parallel resonant circuit, using reactive power compensation principles to reduce the apparent power demand on the power supply side, thereby achieving high-current testing.

[0003] In existing current boosting tests, the energy efficiency assessment of the power output utilization rate mainly relies on static calculation methods. Testers directly use the basic power factor formula to calculate by reading the instantaneous readings of voltage transformers and current transformers. However, the current boosting test of UHV transformers usually lasts for several hours. During this period, as the large current continues to pass through, the transformer windings and external compensation reactors will generate a large amount of Joule heat, which will cause changes in the DC resistance of the windings and slight changes in leakage inductance. This thermoelectric coupling effect makes the equivalent impedance of the current boosting test circuit not a constant value, but a time-varying parameter that drifts nonlinearly with temperature.

[0004] Existing technologies have significant limitations when processing data from long-duration, high-current boosting tests. On the one hand, static calculation methods ignore the dynamic process of impedance drift with temperature, leading to a large deviation between the calculated energy efficiency indicators and the actual system operating state in the middle and later stages of the boosting test. On the other hand, when testers manually adjust the voltage regulator to maintain current stability, the system enters a transient process. Traditional averaging algorithms cannot distinguish between normal adjustment fluctuations and system energy efficiency deterioration, resulting in a lag in the evaluation results. This makes it impossible to guide the on-site switching of compensation capacitors in a timely manner, affecting test efficiency and data accuracy. Summary of the Invention

[0005] To address the aforementioned technical problems of distortion and lag in energy efficiency assessment, this invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides an energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer, comprising: The data acquisition system of the UHV transformer current-increasing test circuit acquires the circuit current, the output voltage on the power supply side, and the transformer oil temperature, and calculates the phase difference and real-time equivalent mode impedance between the circuit current and the output voltage on the power supply side. Based on the transformer oil temperature change rate within a preset data observation window and the fluctuation of the real-time equivalent mode impedance, the thermal drift factor of the current-increasing test circuit is calculated. Dynamic confidence weights are calculated based on the thermal drift factor. The basic energy efficiency value at the current sampling moment is calculated based on the phase difference between the circuit current and the output voltage on the power supply side. Based on the dynamic confidence weights, the basic energy efficiency value at the current moment and the energy efficiency evaluation index at the previous moment are weighted and calculated to obtain the energy efficiency evaluation index at the current moment. An energy efficiency change curve is generated to guide the switching operation of the compensation capacitor in the current-increasing test circuit.

[0007] This invention acquires parameters such as circuit current and transformer oil temperature through a data acquisition system for the current-boosting test circuit of an ultra-high voltage transformer. It then assesses the thermal drift state of the circuit by combining the rate of change of transformer oil temperature and the fluctuation of real-time equivalent modal impedance within the data observation window. Furthermore, it uses calculated dynamic confidence weights to weight the base energy efficiency value at the current moment. During long-term high-current boosting tests of ultra-high voltage transformers, the circuit impedance often experiences nonlinear drift due to thermoelectric coupling effects. Traditional static calculation methods struggle to distinguish between real-world operating condition changes and environmental disturbances. This invention assigns a higher weight to the current data when the system is in a stable state to ensure the sensitivity of the assessment. When thermal drift or transient disturbances occur, the weight of the current data is reduced, and the inertia of historical data is used to maintain the stability of the assessment results. This reduces energy efficiency assessment deviations caused by complex current-boosting test environments or time-varying parameters, making the generated energy efficiency assessment index and energy efficiency change curve more accurately reflect the operating state of the ultra-high voltage transformer during the current-boosting test. This provides on-site test personnel with a reference that balances anti-interference capability and dynamic response speed.

[0008] Preferably, the acquisition of the loop current, the output voltage on the power supply side, and the transformer oil temperature includes: In the current-boosting test circuit of the UHV transformer, the circuit current is collected by a high-precision Hall current sensor or Rogowski coil; the output voltage on the power supply side is collected by a capacitor voltage divider; at the same time, the transformer oil temperature is collected by PT100 temperature sensors embedded in the top and bottom of the transformer tank, and the average value is taken as the transformer oil temperature at the current moment.

[0009] Preferably, the phase difference and real-time equivalent mode impedance between the calculated loop current and the output voltage on the power supply side include: Preprocessing is completed by filtering and denoising the loop current and the output voltage on the power supply side using a sliding median filter. Based on the processed loop current and the output voltage on the power supply side, the phase difference between the loop current and the output voltage on the power supply side is calculated in real time using the zero-crossing detection method, and the real-time equivalent modal impedance of the UHV transformer current-boosting test loop is calculated according to Ohm's law.

[0010] This invention utilizes a sliding median filter to preprocess the acquired loop current and the output voltage on the power supply side, and employs a zero-crossing detection method to obtain the phase relationship. Since the current-boosting test site of UHV transformers is usually in a complex electromagnetic environment, the original acquired signal is easily mixed with random high-frequency noise. Direct calculation may lead to large errors in phase identification. This invention removes environmental interference in advance through a filtering and noise reduction stage, and extracts the phase difference based on waveform characteristics, thereby improving the accuracy of real-time equivalent mode impedance calculation and reducing the risk of distortion in subsequent thermal drift factor calculation due to poor signal quality.

[0011] Preferably, the thermal drift factor satisfies the following relationship: ; In the formula, The thermal drift factor of the current riser test circuit; The transformer oil temperature at the current sampling time; The transformer oil temperature at the start of the data observation window; This represents the total duration of the data observation window; This is the temperature rise weighting coefficient; This is the impedance fluctuation weighting coefficient; For the first data observation window One real-time equivalent modal impedance; For data observation window The arithmetic mean of the real-time equivalent modal impedance; This refers to the length of the data observation window; It is a fundamental constant.

[0012] This invention obtains the thermal drift factor by combining the rate of change of transformer oil temperature per unit time and the dispersion of real-time equivalent modal impedance within the observation window. By introducing a temperature rise weighting coefficient and an impedance fluctuation weighting coefficient, the temperature rise trend in the thermal field and the impedance fluctuation in the electrical field are organically combined, so that the thermal drift factor can sense the unstable state caused by winding heating or external electromagnetic interference.

[0013] Preferably, the settings for the data observation window include: Using the current sampling time as the endpoint, establish a length of A first-in, first-out (FIFO) data observation window is used to store the most recent data. Real-time equivalent modal impedance and transformer oil temperature.

[0014] Preferably, the dynamic confidence weights satisfy the following relationship: ; In the formula, For dynamic confidence weights; The thermal drift factor of the current riser test circuit; It is a non-linear penalty exponent; This is the stable bias constant; This is the sensitivity adjustment constant.

[0015] This invention utilizes a sensitivity adjustment constant and a nonlinear penalty exponent to adaptively adjust the weights. When the thermal drift factor increases, indicating that the loop is in an unstable state, the dynamic confidence weight will automatically decrease by increasing the denominator, thereby suppressing the influence of the current basic energy efficiency value on the final evaluation result. Conversely, when the loop tends to be stable, the weight value increases, thereby automatically adjusting the degree of trust in the measurement data according to the current physical stability, reducing misjudgments caused by instantaneous data fluctuations in unsteady states, while ensuring the ability to follow the actual energy efficiency changes in steady state.

[0016] Preferably, the step of calculating the basic energy efficiency value at the current sampling moment based on the phase difference between the loop current and the output voltage on the power supply side includes: The basic energy efficiency value is equal to the cosine of the phase difference between the loop current and the output voltage on the power supply side.

[0017] Preferably, the energy efficiency assessment index satisfies the following relationship: ; In the formula, This represents the energy efficiency assessment index at the current sampling time. For dynamic confidence weights; This is the baseline energy efficiency value at the current sampling time; This is the energy efficiency assessment index at the previous sampling time.

[0018] This invention dynamically adjusts the proportion of the baseline energy efficiency value at the current moment and the energy efficiency assessment index at the previous moment in the final result through dynamic confidence weights. In the continuous process of UHV transformer current boosting test, when the data reliability is high, it mainly updates based on the current measurement value, while when the data reliability is low, it retains more historical state information. In this way, it uses the historical inertia of the system to smooth out spurious fluctuations caused by thermal effects or transient disturbances, obtains a smoother energy efficiency assessment index that conforms to the laws of physical change, and improves the reliability of test data analysis.

[0019] Preferably, the generation of the energy efficiency change curve to guide the switching operation of the compensation capacitor in the current boost test circuit includes: The calculated energy efficiency assessment index is used to generate an energy efficiency change curve, which is then displayed on a display terminal to guide the switching operation of the compensation capacitor during the test.

[0020] Secondly, the present invention provides an energy efficiency evaluation system for a current-boosting test of an ultra-high voltage transformer, comprising 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 energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer is implemented.

[0021] By adopting the above technical solution, a computer program is generated for the energy efficiency evaluation method of the current boosting test of an ultra-high voltage transformer, and stored in a memory for loading and execution by a processor. Terminal equipment is then manufactured based on the memory and processor for convenient use.

[0022] The beneficial effects of this invention are as follows: This invention comprehensively evaluates the real-time physical stability of the circuit by synchronously collecting multi-dimensional data such as circuit current, voltage, and oil temperature, and combining the transformer oil temperature change rate and the fluctuation degree of real-time equivalent modal impedance within the data observation window. Then, based on this physical stability, dynamic confidence weights are obtained and the proportion of the current basic energy efficiency value in the final evaluation result is adaptively adjusted. When the system is in a steady state, a high-weight strategy is used to ensure the sensitivity of the evaluation result to the actual energy efficiency changes. When the system experiences thermal drift or transient disturbances, the weight of the current data is reduced and the inertia of historical data is used to smooth out spurious fluctuations. This reduces the distortion of energy efficiency evaluation caused by complex test environments, electromagnetic interference, or time-varying parameters, so that the final generated energy efficiency evaluation index can reflect the state changes after the compensation capacitor is switched on and off while suppressing interference. This improves the accuracy and reliability of data analysis in the factory and commissioning tests of UHV transformers. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating an energy efficiency evaluation method for a current boosting test of an ultra-high voltage transformer according to the present invention; Figure 2 This is a schematic diagram illustrating the thermal drift characteristics of transformer impedance. Figure 3 This is a schematic diagram illustrating the principle of the dynamic confidence weight adjustment mechanism; Figure 4 This is a schematic diagram showing a comparison of the energy efficiency evaluation results of the method of the present invention and the prior art. Detailed Implementation

[0024] This invention discloses an energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer, referring to... Figure 1This includes steps S100-S400: S100. The data acquisition system of the UHV transformer current-increasing test circuit obtains the circuit current, the output voltage on the power supply side and the transformer oil temperature, and calculates the phase difference and real-time equivalent modal impedance between the circuit current and the output voltage on the power supply side.

[0025] It should be noted that the electromagnetic environment at the UHV transformer current-increasing test site is complex, and the original acquired signals are often mixed with random high-frequency noise. If used directly for calculation, it will lead to phase identification deviation. Therefore, this invention performs filtering and noise reduction preprocessing on the loop current and the output voltage on the power supply side to eliminate the influence of environmental interference on waveform feature identification. On this basis, the phase difference between the loop current and the output voltage on the power supply side is accurately extracted using waveform feature-based analysis methods, and the real-time equivalent mode impedance of the UHV transformer current-increasing test loop is calculated in combination with Ohm's law, so as to restore the true electrical physical quantities from the interfered signals.

[0026] Specifically, in the current-boosting test circuit of an ultra-high voltage transformer, a high-frequency synchronous data acquisition system is first constructed. Specifically, the circuit current is acquired by a high-precision Hall current sensor or Rogowski coil; the output voltage on the power supply side is acquired by a capacitive voltage divider; at the same time, the transformer oil temperature is acquired by PT100 temperature sensors embedded in the top and bottom of the transformer tank, and the average value is taken as the transformer oil temperature at the current moment; the data sampling frequency is set, for example, the data sampling frequency can be set to 100Hz.

[0027] The loop current and the output voltage on the power supply side are filtered and denoised to complete the preprocessing. Based on the processed loop current and the output voltage on the power supply side, the phase difference between the loop current and the output voltage on the power supply side is calculated in real time using a waveform feature-based analysis method, and the real-time equivalent mode impedance of the UHV transformer current-increasing test loop is calculated according to Ohm's law. For example, the waveform feature-based analysis method is the zero-crossing detection method, and the filtering and denoising uses a sliding median filter; the sliding median filter and the zero-crossing detection method are existing technologies and will not be elaborated upon here.

[0028] For example, Figure 2 The thermal drift characteristics of transformer impedance as oil temperature increases during the current boost test are shown, verifying the existence of thermoelectric coupling effect.

[0029] Thus, the phase difference between the loop current and the output voltage on the power supply side, as well as the real-time equivalent mode impedance, were obtained.

[0030] S200, based on the transformer oil temperature change rate within a preset length data observation window and the fluctuation degree of the real-time equivalent modal impedance, calculates the thermal drift factor of the current-boosting test circuit.

[0031] It should be noted that there is a thermoelectric coupling effect in the current-boosting test circuit of the UHV transformer. As the test time progresses, the heating of the windings and circuit conductors will lead to an increase in DC resistance, and the leakage inductance will also change slightly. This causes the real-time equivalent modal impedance of the UHV transformer current-boosting test circuit to drift nonlinearly with temperature. Therefore, this invention identifies whether the current measurement environment is in a stable state or a thermal drift state by monitoring the transformer oil temperature change rate and the dispersion of the real-time equivalent modal impedance within the real-time monitoring data observation window.

[0032] Specifically, the thermal drift factor of the current-boosting test circuit is calculated based on the transformer oil temperature change rate and the fluctuation of the real-time equivalent modal impedance, including: Using the current sampling time as the endpoint, establish a length of A first-in, first-out (FIFO) data observation window is used to store the most recent data. Real-time equivalent modal impedance and transformer oil temperature. For example, the length of the data observation window... .

[0033] The total duration of the data observation window is obtained by dividing the length of the data observation window by the data sampling frequency.

[0034] Set the temperature rise weighting factor, in units of... The implementers can determine the temperature rise weighting coefficient based on the specific heat capacity of the transformer insulating oil and the slope of the temperature rise curve designed for the current rise test. .

[0035] Set the impedance fluctuation weighting factor, in units of... The implementer can determine the impedance fluctuation weighting factor based on the magnitude of the real-time equivalent modal impedance. .

[0036] The thermal drift factor of the current rise test circuit satisfies the following relationship: ; In the formula, The thermal drift factor of the current riser test circuit; The transformer oil temperature at the current sampling time; The transformer oil temperature at the start of the data observation window; This represents the total duration of the data observation window; This is the temperature rise weighting coefficient, used to normalize the temperature rise rate; This is the impedance fluctuation weighting factor, used to normalize the impedance standard deviation; For the first data observation window One real-time equivalent modal impedance; For data observation window The arithmetic mean of the real-time equivalent modal impedance; This refers to the length of the data observation window; It is a basic constant with a value of 1.0, used to prevent logical anomalies in the formula under ideal isothermal and constant-current conditions.

[0037] In this relation, Indicates the effect of the rate of temperature rise. The larger the value, the faster the transformer oil temperature changes within the observation window, and the system is in a rapidly heating unsteady state. The standard deviation of the real-time equivalent mode impedance represents the degree of fluctuation of the real-time equivalent mode impedance. The larger the standard deviation, the higher the dispersion of the loop impedance under the action of thermal effects, and the more unstable the measurement environment.

[0038] For example, suppose the total duration of the data observation window is... The length of the data observation window The sampling frequency is 100Hz; the transformer oil temperature at the current sampling time. Transformer oil temperature at the start of the data observation window The standard deviation of the real-time equivalent modal impedance within the data observation window is: Set the temperature rise weighting coefficient. Impedance fluctuation weighting coefficient Fundamental constants The thermal drift factor of the current riser test circuit is: .

[0039] Thus, the thermal drift factor of the upflow test circuit was obtained.

[0040] S300, Calculate the dynamic confidence weight based on the thermal drift factor of the current rise test circuit.

[0041] It should be noted that the calculated thermal drift factor of the current-boosting test circuit reflects the current physical instability of the UHV transformer current-boosting test circuit. In order to prevent the current basic energy efficiency value from being used entirely for energy efficiency calculation when the system is in an unsteady state due to severe thermal drift or external disturbances, which would lead to large false fluctuations in the evaluation results, this invention transforms the thermal stability at the physical level into a dynamic confidence weight at the algorithm level. Thus, when the system experiences severe thermal drift, the weight of the current basic energy efficiency value is automatically reduced to suppress disturbances, and the weight is increased when the system is stable to reflect the true changes.

[0042] Specifically, the dynamic confidence weights are calculated based on the thermal drift factor of the current rise test circuit, and the dynamic confidence weights satisfy the following relationship: ; In the formula, For dynamic confidence weights; The thermal drift factor of the current riser test circuit; It is a non-linear penalty exponent used to amplify the penalty intensity under high drift conditions; To stabilize the bias constant, it can be set to 0.1 to prevent the denominator from being 0; Let be the sensitivity adjustment constant, and its value satisfies . , It is a basic constant to ensure that the weight is 1 in the most ideal stable state.

[0043] In this relationship, when the thermal drift factor of the current riser test circuit increases, it indicates that the system is unstable. Increasing the value of the current data leads to a decrease in the dynamic confidence weight, thereby suppressing the weight of the current data; conversely, decreasing the thermal drift factor of the current rise test loop reduces the current and approaches the fundamental constant. When this occurs, it indicates that the system is approaching stability. The reduction leads to an increase in the dynamic confidence weight, which approaches 1, making the energy efficiency assessment results more sensitive to the actual measurement values.

[0044] For example, the thermal drift factor of the current rise test circuit Set a nonlinear penalty index Stable bias constant Then the sensitivity adjustment constant The calculated dynamic confidence weights are: .

[0045] For example, Figure 3 The study demonstrates the regulatory mechanism of dynamic confidence weights as a function of thermal drift factor, showing a clear inverse logical relationship between the two.

[0046] Thus, the dynamic confidence weights were obtained.

[0047] S400: Calculate the basic energy efficiency value at the current sampling moment based on the phase difference between the loop current and the output voltage on the power supply side; calculate the energy efficiency evaluation index at the current moment by weighting the basic energy efficiency value at the current moment and the energy efficiency evaluation index at the previous moment based on dynamic confidence weight; and generate an energy efficiency change curve to guide the switching operation of the compensation capacitor in the current boost test circuit.

[0048] It should be noted that in the energy efficiency assessment of UHV transformer current-up tests, if the current baseline energy efficiency value is used, the assessment curve is easily affected by thermal drift and electromagnetic interference, resulting in spikes. If a fixed-parameter average filter is used, it cannot reflect the state changes caused by the switching of compensation capacitors in a timely manner. Therefore, this invention uses calculated dynamic confidence weights to intervene in the filtering process in real time, adjusting the proportion of the current baseline energy efficiency value and the energy efficiency assessment index of the previous moment in the final result. When the data reliability is high, this invention makes the algorithm mainly follow the current baseline energy efficiency value to ensure high sensitivity. When the data reliability is low, this invention makes the algorithm mainly maintain the energy efficiency assessment index of the previous moment to use system inertia to suppress spurious fluctuations and ensure that the final output energy efficiency assessment index is smooth.

[0049] Specifically, based on the phase difference between the loop current and the output voltage on the power supply side, the baseline energy efficiency value at the current sampling moment is calculated, and the baseline energy efficiency value satisfies the following relationship: ; In the formula, This is the phase difference between the loop current and the output voltage on the power supply side; It is a cosine function.

[0050] Preferably, the energy efficiency assessment index at the current sampling time is calculated based on the basic energy efficiency value and dynamic confidence weight, and the energy efficiency assessment index satisfies the following relationship: ; In the formula, This represents the energy efficiency assessment index at the current sampling time. For dynamic confidence weights; This is the baseline energy efficiency value at the current sampling time; This is the energy efficiency assessment index at the previous sampling time.

[0051] In this relation, This represents the contribution of the phase difference at the current sampling moment to the energy efficiency assessment index at the current sampling moment. This represents the contribution of the energy efficiency assessment index at the previous sampling time to the energy efficiency assessment index at the current sampling time. When the system is stable, the dynamic confidence weight approaches 1, and the energy efficiency assessment index at the current sampling time is mainly determined by the phase difference at the current sampling time. The assessment result can quickly follow the actual changes in the system and has high sensitivity. When the system experiences thermal drift or disturbance, the dynamic confidence weight approaches 0. Approaching 1, the energy efficiency assessment index at the current sampling time mainly maintains the energy efficiency assessment index at the previous time, exhibiting anti-interference inertia, thereby suppressing spurious fluctuations caused by thermal effects.

[0052] It should be noted that at the initial moment, it can be set to... .

[0053] For example, the calculated dynamic confidence weights are: Assuming a base energy efficiency value The final energy efficiency assessment index at the previous sampling time The energy efficiency assessment index at the current moment is: .

[0054] The calculation results show that although the phase difference between the current loop current and the output voltage on the power supply side suddenly drops to 37°, the thermal drift factor identifies the system as being in an unstable state and assigns a low dynamic confidence weight. Therefore, the energy efficiency assessment index is [insert value here]. Only a slight decrease occurred, maintaining consistency with the previous value of 0.9 and suppressing spurious energy efficiency fluctuations. If the system is in a stable state and the dynamic confidence weight is close to 1, the energy efficiency assessment index at the current sampling time will be close to the basic energy efficiency value, improving the sensitivity of the response.

[0055] Preferably, the calculated energy efficiency assessment index is used to generate an energy efficiency change curve, which is then displayed on a display terminal to guide the switching operation of the compensation capacitor during the test.

[0056] Thus, the energy efficiency assessment index and energy efficiency change curve at the current sampling time were obtained.

[0057] This invention also discloses an energy efficiency evaluation system for an ultra-high voltage transformer current-boosting test, comprising a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement an energy efficiency evaluation method for an ultra-high voltage transformer current-boosting test according to the present invention.

[0058] For example, Figure 4 The evaluation results of the method of this invention were compared with those of the traditional static calculation method. The existing technology showed drastic fluctuations and was full of spikes, while the method of this invention produced a smooth curve and could accurately reflect the real trend of energy efficiency changes, proving the effectiveness of this solution under complex working conditions.

[0059] 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.

[0060] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. A method for evaluating the energy efficiency of an ultra-high voltage transformer current-boosting test, characterized in that, include: The data acquisition system of the UHV transformer current boosting test circuit obtains the circuit current, the output voltage on the power supply side and the transformer oil temperature, and calculates the phase difference and real-time equivalent modal impedance between the circuit current and the output voltage on the power supply side. Based on the transformer oil temperature change rate within a preset data observation window and the fluctuation degree of the real-time equivalent modal impedance, the thermal drift factor of the current boost test circuit is calculated; and the dynamic confidence weight is calculated based on the thermal drift factor. Thermal drift factor satisfy: ； The transformer oil temperature at the current sampling time; The transformer oil temperature at the start of the data observation window; This represents the total duration of the data observation window; This is the temperature rise weighting coefficient; This is the impedance fluctuation weighting coefficient; For the first data observation window One real-time equivalent modal impedance; For data observation window The arithmetic mean of the real-time equivalent modal impedance; This refers to the length of the data observation window; Basic constants; Dynamic confidence weights satisfy: ； It is a non-linear penalty exponent; This is the stable bias constant; Sensitivity adjustment constant Calculate the basic energy efficiency value at the current sampling moment based on the phase difference between the loop current and the output voltage on the power supply side; Based on dynamic confidence weights, the current baseline energy efficiency value and the energy efficiency assessment index of the previous time are weighted and calculated to obtain the current energy efficiency assessment index; and an energy efficiency change curve is generated to guide the switching operation of the compensation capacitor in the current rise test circuit.

2. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The acquisition of loop current, power supply side output voltage, and transformer oil temperature includes: In the current-boosting test circuit of the UHV transformer, the circuit current is collected by a high-precision Hall current sensor or Rogowski coil; the output voltage on the power supply side is collected by a capacitor voltage divider; at the same time, the transformer oil temperature is collected by PT100 temperature sensors embedded in the top and bottom of the transformer tank, and the average value is taken as the transformer oil temperature at the current moment.

3. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The phase difference and real-time equivalent mode impedance between the calculated loop current and the output voltage on the power supply side include: Preprocessing is completed by filtering and denoising the loop current and the output voltage on the power supply side using a sliding median filter. Based on the processed loop current and the output voltage on the power supply side, the phase difference between the loop current and the output voltage on the power supply side is calculated in real time using the zero-crossing detection method, and the real-time equivalent modal impedance of the UHV transformer current-boosting test loop is calculated according to Ohm's law.

4. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The settings for the data observation window include: Using the current sampling time as the endpoint, establish a length of A first-in, first-out (FIFO) data observation window is used to store the most recent data. Real-time equivalent modal impedance and transformer oil temperature.

5. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The calculation of the baseline energy efficiency value at the current sampling moment based on the phase difference between the loop current and the output voltage on the power supply side includes: The basic energy efficiency value is equal to the cosine of the phase difference between the loop current and the output voltage on the power supply side.

6. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The energy efficiency assessment index satisfies the following relationship: ； In the formula, This represents the energy efficiency assessment index at the current sampling time. For dynamic confidence weights; This is the baseline energy efficiency value at the current sampling time; This is the energy efficiency assessment index at the previous sampling time.

7. The energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to claim 1, characterized in that, The generation of the energy efficiency change curve to guide the switching operation of the compensation capacitor in the current-boosting test circuit includes: The calculated energy efficiency assessment index is used to generate an energy efficiency change curve, which is then displayed on a display terminal to guide the switching operation of the compensation capacitor during the test.

8. An energy efficiency evaluation system for current boosting tests of ultra-high voltage transformers, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement an energy efficiency evaluation method for a current-boosting test of an ultra-high voltage transformer according to any one of claims 1-7.

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