Capacitive voltage transformer measurement deviation evaluation method and system

Abstract

The invention provides a measurement deviation evaluation method and system for a capacitor voltage transformer, and relates to the technical field of state evaluation and fault diagnosis of power transmission and distribution equipment. Performing feature extraction on the working data to obtain voltage feature data and magnetic field feature data of the voltage transformer, analyzing the voltage feature data to generate a first measurement deviation evaluation coefficient, and analyzing the magnetic field feature data to generate a magnetic field correction factor; correcting the first measurement deviation evaluation coefficient by using the magnetic field correction factor to obtain a second measurement deviation evaluation coefficient; analyzing the environmental data to generate a performance attenuation coefficient, and generating a measurement deviation evaluation index according to the performance attenuation coefficient and the second measurement deviation evaluation coefficient; the measurement deviation state is classified into a normal state and an abnormal state by performing threshold analysis on the generated measurement deviation evaluation index.

Description

Technical Field

[0001] The present invention relates to the technical field of state assessment and fault diagnosis of power transmission and distribution equipment, and in particular to a method and system for assessing measurement deviation of a capacitive voltage transformer. Background Art

[0002] Capacitor voltage transformers (CVTs) are widely used in high-voltage power systems, mainly for voltage measurement, protection, and signal transmission. However, due to the complexity of the power system operating environment, the measurement accuracy of CVTs is often affected by many factors. For example, changes in temperature and humidity may significantly affect the performance of capacitors, resulting in deviations in the output voltage. In addition, external electromagnetic interference may also cause instability in the output signal, thereby affecting the accuracy of the measurement results. As the equipment is used for a longer time, aging and wear will also increase, causing changes in the original measurement characteristics, further increasing the measurement error. These problems pose potential risks to the safe operation of the power system and may lead to system failures or power supply interruptions.

[0003] Existing measurement deviation assessment methods often rely on manual monitoring and regular maintenance, and lack real-time monitoring and assessment of equipment status. Traditional assessment methods usually use simple linear models, which fail to fully consider the interaction of multiple factors, resulting in insufficient accuracy and reliability of the assessment results. This method is not only difficult to cope with complex power system environments, but may also miss early warning opportunities for failures, increasing maintenance costs and system risks. Therefore, a more comprehensive and systematic measurement deviation assessment method is urgently needed to address the deficiencies in current technology.

[0004] In the prior art, the publication number CN112485747A discloses a method for evaluating the error state of a capacitor voltage transformer, which collects the output voltage of a three-phase capacitor voltage transformer in a healthy state, and uses a high-dimensional random matrix analysis method to establish a threshold value of a statistical characteristic parameter characterizing the error state of the capacitor voltage transformer and a statistical characteristic quantity of a normal operating state; the output voltage of the three-phase capacitor voltage transformer after commissioning is collected, and the statistical characteristic quantity characterizing the error state of the three-phase capacitor voltage transformer is calculated, and compared with the statistical threshold value to determine whether the error state of the capacitor voltage transformer is normal. This prior art realizes the evaluation of the error state of the capacitor voltage transformer without power outage, without relying on a standard device and a physical model. However, this prior art still has defects. This prior art only analyzes the working voltage data of the voltage transformer, and ignores the aging of the voltage transformer's own performance and the influence of the surrounding environment on the voltage transformer measurement error, which will cause the accuracy of the relevant parameters for the measurement error state evaluation to be insufficient, resulting in unreliable final evaluation results.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The object of the present invention is to provide a method and system for evaluating measurement deviation of a capacitor voltage transformer to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method and system for evaluating measurement deviation of a capacitor voltage transformer, the specific steps comprising:

[0009] Step 1: Collecting working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer;

[0010] Step 2: extracting features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate;

[0011] Step 3: Generate a first measurement deviation evaluation coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain a second measurement deviation evaluation coefficient;

[0012] Step 4: Perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; preset a measurement deviation evaluation threshold, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state.

[0013] Furthermore, the specific logic for obtaining voltage characteristic data is as follows: the optimal time delay of voltage time series data is determined by the autocorrelation function of voltage time series data, the voltage time series data is reconstructed in phase space by the optimal time delay, the trajectory of the phase space of any two phases is subjected to chaos analysis to obtain the Lyapunov index, and then the Lyapunov index between each phase is averaged to obtain the average Lyapunov index, and then the voltage time series data is subjected to complexity and uncertainty analysis in the phase space to obtain the voltage approximate index; the specific logic for obtaining the optimal time delay is as follows: the first minimum value of the autocorrelation function is defined as the optimal time delay, and the selected autocorrelation function formula is:

[0014]

[0015] R(τ) is the autocorrelation function of the voltage time series data, u(t) is the voltage time series data, u(t-τ) is the voltage time series data after adding time delay, and τ is the time delay.

[0016] The specific formula for phase space reconstruction of voltage time series data is as follows:

[0017] X(t)=[u(t),u(t+τ 0 ), u(t+2τ 0 )…u(t+(m-1)τ 0 )]m∈N + , m<N

[0018] Where X(t) is the phase space reconstruction vector of the voltage time series data, u(t+(m-1)τ 0 is the m-dimensional voltage time series data; m is the number of embedding dimensions, N is the length of the time series data, τ 0 The best delay.

[0019] Furthermore, the specific logic for extracting the voltage approximation index is as follows: calculate the Euclidean distance at each time point between any two phases, preset a tolerance r, and when the Euclidean distance at each time point between the two phases is less than the tolerance r, define the corresponding points as similar points, remove the non-similar points in the data, and count the total time length of all similar points. Divide the total time length of the similar points between every two phases of the three phases by the total time length of the time series data, and then perform the mean operation to obtain the voltage approximation index. The specific formula for generating the voltage approximation index is as follows:

[0020]

[0021] Where p is the voltage approximation index, T is the total time length of the time series data, and T AB is the total time length of the similar points between AB, T BC is the total time length of the similar points of BC, TAC is the total time length of the AC similarity points.

[0022] Furthermore, the specific logic for generating the first measurement deviation evaluation coefficient is: performing mathematical analysis on the voltage characteristic data to generate the first measurement deviation evaluation coefficient, and the specific formula for generating the first measurement deviation evaluation coefficient is:

[0023]

[0024] Wherein, El is the first measurement deviation evaluation coefficient, is the average Lyapunov exponent, and p is the voltage approximation exponent.

[0025] Furthermore, the specific logic for generating the second measurement deviation evaluation coefficient is: analyzing the magnetic field characteristic data to generate a magnetic field correction factor, and using the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain the second measurement deviation evaluation coefficient; the specific formula for generating the magnetic field correction factor is:

[0026]

[0027] Among them, Ev is the magnetic field correction factor, THD is the total harmonic interference rate, Tn is the spectrum flatness, is the maximum magnetic field change rate;

[0028] The specific formula for generating the second measurement deviation evaluation coefficient is:

[0029]

[0030] Wherein, Eb is the second measurement deviation evaluation coefficient, El is the first measurement deviation evaluation coefficient, and Ev is the magnetic field correction factor.

[0031] Furthermore, the specific logic for evaluating the measurement deviation state of the capacitor voltage transformer is as follows: mathematically analyzing the capacitor voltage transformer environmental data to generate a performance attenuation coefficient, and generating a measurement deviation evaluation index according to the performance attenuation coefficient and the second measurement deviation evaluation coefficient; presetting a measurement deviation evaluation threshold, classifying the capacitor voltage transformer measurement deviation state whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classifying the capacitor voltage transformer measurement deviation state whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state; the specific formula for generating the performance attenuation coefficient is as follows:

[0032] θ=e Tt *Tw*tan -1 We

[0033] Among them, θ is the performance attenuation coefficient, Tt is the delivery time, Tw is the daily average temperature data, and We is the mean of the daily average humidity data;

[0034] The specific formula used to generate the measurement bias assessment index is:

[0035]

[0036] Among them, Ee is the measurement deviation evaluation index, and Eb is the second measurement deviation evaluation coefficient.

[0037] The present invention further provides a capacitor voltage transformer measurement deviation evaluation system, the system is used to implement the capacitor voltage transformer measurement deviation evaluation method, specifically comprising:

[0038] A data acquisition module is used to collect working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer;

[0039] A feature extraction module is used to extract features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate;

[0040] An error assessment module, used to generate a first measurement deviation assessment coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation assessment coefficient to obtain a second measurement deviation assessment coefficient;

[0041] The state evaluation module is used to perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and to generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; a measurement deviation evaluation threshold is preset, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold is classified as a normal state, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold is classified as an abnormal state.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention is based on; the present invention not only considers the voltage time series data, but also adds the analysis of environmental factors such as magnetic field strength, temperature, humidity, etc. The analysis of voltage and magnetic field characteristic data is introduced, and a multi-dimensional comprehensive evaluation model is established in combination with environmental factors and equipment aging status, thereby effectively improving the accuracy of the evaluation. This method can dynamically correct the measurement deviation caused by environmental changes and equipment aging, ensuring the reliability of the evaluation results under various operating conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the overall method flow of the present invention.

[0045] Figure 2 It is a schematic diagram of the overall system structure of the present invention. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0047] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0048] Example:

[0049] See also Figure 1 , the present invention provides a technical solution:

[0050] A method for evaluating measurement deviation of a capacitor voltage transformer, the specific steps comprising:

[0051] Step 1: Collecting working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer;

[0052] The voltage time series data is collected by a data acquisition card installed on the three-phase capacitive voltage transformer, the magnetic field strength time series data is collected by a magnetic field sensor installed on the three-phase capacitive voltage transformer, the release time is obtained by querying the installation record, and the temperature data and humidity data are obtained by querying the weather forecast data of the local meteorological station.

[0053] Step 2: Extracting features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate;

[0054] The specific logic for obtaining voltage characteristic data is as follows: determine the optimal time delay of voltage time series data through the autocorrelation function of voltage time series data, reconstruct the voltage time series data in phase space through the optimal time delay, perform chaos analysis on the trajectory of phase space to obtain the average Lyapunov index, and then perform complexity and uncertainty analysis on the voltage time series data in phase space to obtain the voltage approximate index; the specific logic for obtaining the optimal time delay is as follows: define the first minimum value of the autocorrelation function as the optimal time delay, and the selected autocorrelation function formula is:

[0055]

[0056] R(τ) is the autocorrelation function of the voltage time series data, u(t) is the voltage time series data, u(t-τ) is the voltage time series data after adding time delay, and τ is the time delay.

[0057] The specific formula for phase space reconstruction of voltage time series data is as follows:

[0058] X(t)=[u(t),u(t+τ 0 ), u(t+2τ 0 )…u(t+(m-1)τ 0 )]m∈N + , m<N

[0059] Where X(t) is the phase space reconstruction vector of the voltage time series data, u(t+(m-1)τ 0 is the m-dimensional voltage time series data; m is the number of embedding dimensions, N is the length of the time series data, τ 0 The best delay.

[0060] The specific logic for extracting the voltage approximation index is as follows: calculate the Euclidean distance between any two phases at each time point, preset a tolerance r, and when the Euclidean distance between the two phases at each time point is less than the tolerance r, define the corresponding points as similar points, remove the non-similar points in the data, and count the total time length of all similar points. Divide the total time length of the similar points between each two phases of the three phases by the total time length of the time series data, and then perform the mean operation to obtain the voltage approximation index. The specific formula for generating the voltage approximation index is as follows:

[0061]

[0062] Where p is the voltage approximation index, T is the total time length of the time series data, and T AB is the total time length of the similar points between AB, T BC is the total time length of the similar points of BC, T AC is the total time length of the AC phase similarity point. p reflects the similarity between the phases of the three-phase circuit. The larger its value is, the higher the similarity of the three circuit voltages is, and the less likely it is to produce measurement deviations.

[0063] Step 3: Generate a first measurement deviation evaluation coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain a second measurement deviation evaluation coefficient;

[0064] The specific logic for generating the first measurement deviation evaluation coefficient is: performing mathematical analysis on the voltage characteristic data to generate the first measurement deviation evaluation coefficient, and the specific formula for generating the first measurement deviation evaluation coefficient is:

[0065]

[0066] Wherein, El is the first measurement deviation evaluation coefficient, is the average Lyapunov index, and p is the voltage approximation index. The first measurement deviation evaluation coefficient El reflects the measurement error generated in the working mode of the capacitor voltage transformer. The larger its value, the greater the measurement error generated. Average Lyapunov index It reflects the comprehensive stability of the three-phase system. When it is a positive number, the larger its value is, the more sensitive the phase space is to the internal orbit, and the more chaotic the system is. When it is a negative number, the larger its value is, the more sensitive the phase space is to the internal orbit, and the more stable the system is.

[0067] The specific logic for generating the second measurement deviation evaluation coefficient is: analyzing the magnetic field characteristic data to generate a magnetic field correction factor, and using the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain the second measurement deviation evaluation coefficient; the specific formula for generating the magnetic field correction factor is:

[0068]

[0069] Among them, Ev is the magnetic field correction factor, THD is the total harmonic interference rate, Tn is the harmonic flatness, The maximum magnetic field change rate; the magnetic field correction factor Ev reflects the influence of the magnetic field around the capacitive voltage transformer on the measurement error. The larger its value, the smaller the measurement deviation. The harmonic interference rate THD reflects the relative strength of the harmonic components in the magnetic field. The larger its value, the more harmonic components there are in the signal. The spectrum flatness Tn reflects the distribution of the signal. The larger its value, the flatter the magnetic field frequency distribution. In this case, the probability of measurement error is lower. Maximum magnetic field change rate It reflects the extreme conditions of the magnetic field changes around the capacitive voltage transformer. The larger the value, the easier it is to cause measurement errors.

[0070] The specific formula for generating the second measurement deviation evaluation coefficient is:

[0071]

[0072] Among them, Eb is the second measurement deviation evaluation coefficient, El is the first measurement deviation evaluation coefficient, and Ev is the magnetic field correction factor. The second measurement deviation evaluation coefficient Eb reflects the situation of measurement error under a certain capacitive voltage transformer working mode considering the surrounding magnetic field. The larger its value, the greater the measurement error. The generation of this coefficient can provide an important basis for the evaluation of the secondary beam error.

[0073] Step 4: Perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; preset a measurement deviation evaluation threshold, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state.

[0074] The specific logic for evaluating the measurement deviation state of the capacitor voltage transformer is as follows: mathematically analyzing the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and generating a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; presetting a measurement deviation evaluation threshold, classifying the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classifying the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state; the specific formula for generating the performance attenuation coefficient is as follows:

[0075] θ=e Tt *Tw*tan -1 We

[0076] Among them, θ is the performance attenuation coefficient, Tt is the delivery time, Tw is the daily average temperature data, and We is the mean of the daily average humidity data;

[0077] The performance attenuation coefficient θ reflects the performance attenuation of the capacitor voltage transformer caused by the surrounding environmental factors since it was put into use. The larger the value, the more serious the performance attenuation of the capacitor voltage transformer, and the easier it is to produce measurement errors.

[0078] The specific formula used to generate the measurement bias assessment index is:

[0079]

[0080] Among them, Ee is the measurement deviation evaluation index, Eb is the second measurement deviation evaluation coefficient, and the measurement deviation evaluation index Ee comprehensively reflects the situation of measurement error. The larger its value is, the greater the measurement error is.

[0081] See also Figure 2 The present invention further provides a capacitor voltage transformer measurement deviation evaluation system, the system is used to implement the capacitor voltage transformer measurement deviation evaluation method, specifically comprising:

[0082] A data acquisition module is used to collect working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer;

[0083] A feature extraction module is used to extract features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate;

[0084] An error assessment module, used to generate a first measurement deviation assessment coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation assessment coefficient to obtain a second measurement deviation assessment coefficient;

[0085] The state evaluation module is used to perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and to generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; a measurement deviation evaluation threshold is preset, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold is classified as a normal state, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold is classified as an abnormal state.

[0086] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0087] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0088] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A method for evaluating measurement deviation of a capacitor voltage transformer, characterized in that: The specific steps include: Step 1: Collecting working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer; Step 2: extracting features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate; Step 3: Generate a first measurement deviation evaluation coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain a second measurement deviation evaluation coefficient; Step 4: Perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; preset a measurement deviation evaluation threshold, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classify the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state.

2. A method for evaluating measurement deviation of a capacitor voltage transformer according to claim 1, characterized in that: The specific logic for obtaining voltage characteristic data is as follows: determine the optimal time delay of voltage time series data through the autocorrelation function of voltage time series data, reconstruct the phase space of voltage time series data through the optimal time delay, perform chaos analysis on the trajectory of phase space of any two phases to obtain the Lyapunov index, then perform average calculation on the Lyapunov index between each phase to obtain the average Lyapunov index, and then perform complexity and uncertainty analysis on voltage time series data in phase space to obtain the voltage approximate index; the specific logic for obtaining the optimal time delay is as follows: define the first minimum value of the autocorrelation function as the optimal time delay, and the selected autocorrelation function formula is: R(τ) is the autocorrelation function of the voltage time series data, u(t) is the voltage time series data, u(t-τ) is the voltage time series data after adding time delay, and τ is the time delay; The specific formula for phase space reconstruction of voltage time series data is as follows: X(t)=[u(t),u(t+τ0),u(t+2τ0)…u(t+(m-1)τ0)]m∈N + ,m<N Among them, X(t) is the phase space reconstruction vector of the voltage time series data, u(t+(m-1)τ0 is the m-dimensional voltage time series data, m is the number of embedding dimensions, N is the length of the time series data, and τ0 is the optimal delay.

3. A method for evaluating measurement deviation of a capacitor voltage transformer according to claim 2, characterized in that: The specific logic for extracting the voltage approximation index is as follows: calculate the Euclidean distance between any two phases at each time point, preset a tolerance r, and when the Euclidean distance between the two phases at each time point is less than the tolerance r, define the corresponding points as similar points, remove the non-similar points in the data, and count the total time length of all similar points. Divide the total time length of the similar points between each two phases of the three phases by the total time length of the time series data, and then perform the mean operation to obtain the voltage approximation index. The specific formula for generating the voltage approximation index is as follows: Where p is the voltage approximation index, T is the total time length of the time series data, and T AB is the total time length of the similar points between AB, T BC is the total time length of the similar points of BC, T AC is the total time length of the AC similarity points.

4. The method for evaluating measurement deviation of a capacitor voltage transformer according to claim 1, characterized in that: The specific logic for generating the first measurement deviation evaluation coefficient is: performing mathematical analysis on the voltage characteristic data to generate the first measurement deviation evaluation coefficient, and the specific formula for generating the first measurement deviation evaluation coefficient is: Wherein, El is the first measurement deviation evaluation coefficient, is the average Lyapunov exponent, and p is the voltage approximation exponent.

5. A method for evaluating measurement deviation of a capacitor voltage transformer according to claim 1, characterized in that: The specific logic for generating the second measurement deviation evaluation coefficient is: analyzing the magnetic field characteristic data to generate a magnetic field correction factor, and using the magnetic field correction factor to correct the first measurement deviation evaluation coefficient to obtain the second measurement deviation evaluation coefficient; the specific formula for generating the magnetic field correction factor is: Among them, Ev is the magnetic field correction factor, THD is the total harmonic interference rate, Tn is the spectrum flatness, is the maximum magnetic field change rate; The specific formula for generating the second measurement deviation evaluation coefficient is: Wherein, Eb is the second measurement deviation evaluation coefficient, El is the first measurement deviation evaluation coefficient, and Ev is the magnetic field correction factor.

6. A method for evaluating measurement deviation of a capacitor voltage transformer according to claim 1, characterized in that: The specific logic for evaluating the measurement deviation state of the capacitor voltage transformer is as follows: preprocessing the environmental data of the capacitor voltage transformer, mathematically analyzing the preprocessed environmental data to generate a performance attenuation coefficient, and generating a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; presetting a measurement deviation evaluation threshold, classifying the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold as a normal state, and classifying the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold as an abnormal state; the specific formula for generating the performance attenuation coefficient is as follows: θ=e Tt *Tw*tan -1 We Among them, θ is the performance attenuation coefficient, Tt is the delivery time, Tw is the daily average temperature data, and We is the mean of the daily average humidity data: The specific formula used to generate the measurement bias assessment index is: Among them, Ee is the measurement deviation evaluation index, and Eb is the second measurement deviation evaluation coefficient.

7. A capacitor voltage transformer measurement deviation evaluation system, characterized in that: The system is used to implement the capacitor voltage transformer measurement deviation evaluation method according to any one of claims 1 to 6, and specifically includes: A data acquisition module is used to collect working data and environmental data of the capacitor voltage transformer; the working data includes the output voltage time series data and magnetic field strength time series data of each phase of the three-phase capacitor voltage transformer; the environmental data includes the daily average temperature time series data, the daily average humidity time series data and the delivery time at the capacitor voltage transformer; A feature extraction module is used to extract features from the working data of the capacitive voltage transformer to obtain voltage feature data and magnetic field feature data of the voltage transformer, wherein the voltage feature data includes an average Lyapunov index and a voltage approximation index; and the magnetic field feature data includes a maximum magnetic field change rate, a spectrum flatness, and a harmonic interference rate; An error assessment module, used to generate a first measurement deviation assessment coefficient by mathematically analyzing the voltage characteristic data, generate a magnetic field correction factor by analyzing the magnetic field characteristic data, and use the magnetic field correction factor to correct the first measurement deviation assessment coefficient to obtain a second measurement deviation assessment coefficient; The state evaluation module is used to perform mathematical analysis on the environmental data of the capacitor voltage transformer to generate a performance attenuation coefficient, and to generate a measurement deviation evaluation index based on the performance attenuation coefficient and the second measurement deviation evaluation coefficient; a measurement deviation evaluation threshold is preset, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is greater than the measurement deviation evaluation threshold is classified as a normal state, and the measurement deviation state of the capacitor voltage transformer whose measurement deviation evaluation index is less than or equal to the measurement deviation evaluation threshold is classified as an abnormal state.

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