Device and method for quickly compensating voltage in power distribution area based on controllable series compensation

Abstract

The invention relates to the technical field of controllable series compensation, in particular to a power distribution area voltage rapid compensation device and compensation method based on controllable series compensation, and the method comprises the steps: collecting various monitoring data of each phase of each key node of a power distribution area in real time; obtaining each sub-time period of each monitoring data of each phase; acquiring a change correlation value and a deviation change characteristic value of various monitoring data of each phase in each sub-time period; comparing the deviation change characteristic values of various monitoring data between each phase and each of the other phases of the key node where the phase is located so as to obtain a dynamic change factor of the various monitoring data of each phase at each moment and obtain an influence weight and a voltage characteristic value of each phase of each key node at each moment; and compensating the voltage of the power distribution area based on a controllable series compensation technology. According to the method, the trigger angle in the voltage compensation process is accurately determined by accurately evaluating the voltage deviation of each key node, and the accuracy of voltage compensation of the power distribution area is improved.

Description

Technical Field

[0001] This application relates to the field of controllable series compensation technology, specifically to a fast voltage compensation device and method for distribution radio stations based on controllable series compensation. Background Technology

[0002] During the operation of a distribution substation, the voltage quality at the user end of the distribution network is a core factor affecting the safety of power equipment. With changes in the load structure of the distribution substation, the impact loads and line impedance generated during the seasonal start-up and shutdown of cluster motors can cause voltage drops and three-phase load imbalances, leading to voltage dips and excessive deviations in the distribution substation. This affects motor starting and normal equipment operation, and increases line losses. Controllable series compensation technology can achieve rapid voltage compensation by injecting a controllable compensation voltage in series, quickly correcting voltage deviations and thus suppressing the impact of load fluctuations on voltage.

[0003] However, in the current process of rapid voltage compensation for distribution transformer substations based on controllable series compensation technology, the monitoring and compensation accuracy of the substations is low due to seasonal load characteristics and line impedance changes, which affects the operational stability of the substations. Specifically, because the dynamic characteristics of voltage sags and swells, as well as the dynamic characteristics of seasonal load characteristics and line impedance, are not analyzed during the operation of the substations, the voltage regulation and voltage compensation requirements based on thyristor controlled series capacitors (TCSC) deviate significantly from the requirements. This causes the firing angle adjustment to be out of sync with the load characteristics, resulting in over- or under-compensation of voltage compensation during the voltage compensation process, which fails to meet the precise voltage compensation requirements of the distribution transformer substations. Summary of the Invention

[0004] In view of the above, it is necessary to provide a fast voltage compensation device and method for distribution transformer substations based on controllable series compensation. Compared with the traditional fast voltage compensation method for distribution transformer substations based on controllable series compensation, this method improves the accuracy of voltage compensation by accurately assessing the voltage deviation of each key node and precisely determining the firing angle during the voltage compensation process. In a first aspect, embodiments of this application provide a method for rapid voltage compensation in distribution radio stations based on controllable series compensation, the method comprising the following steps: Real-time acquisition of various monitoring data for each phase of each key node in the distribution radio area; By analyzing the differences between various monitoring data of each phase and their rated values, we obtain the sub-periods of various monitoring data of each phase. By analyzing the correlation between the changes of various monitoring data of each phase and each other phase of the key node in each sub-period, we obtain the correlation values ​​of the changes of various monitoring data of each phase in each sub-period. In addition, by combining the correlation between various monitoring data of each phase and each other monitoring data in each sub-period, as well as the differences between various monitoring data of each phase and their rated values ​​in each sub-period, we obtain the characteristic values ​​of the deviation changes of various monitoring data of each phase in each sub-period. By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases of its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time are obtained. Then, the influence weight of each phase of each key node at each time is obtained. Finally, combined with the difference between the voltage data of each phase of each key node at each time and its rated value, the voltage characteristic value of each key node at each time is obtained, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

[0005] In one embodiment, the process of obtaining the sub-time period is as follows: Calculate the difference between various monitoring data and their rated values ​​at each time point. Arrange the difference between the k-th monitoring data of phase j and its rated value in the local time period before each time point according to time sequence and perform curve fitting. Take the time of each extreme point in the fitted curve as the dividing point and divide the local time period before each time point into sub-time periods of the k-th monitoring data of phase j.

[0006] In one embodiment, the process of obtaining the change-related value is as follows: The differences between various monitoring data at each time point and its adjacent time points are recorded as the changes in various monitoring data at each time point; Within each sub-period of the k-th monitoring data in phase j, calculate the absolute value of the correlation coefficient between phase j and each of the other phases for the change value of the k-th monitoring data at all times. Take the mean of the absolute values ​​of the correlation coefficients between phase j and all other phases of the key node as the change correlation value of the k-th monitoring data in phase j within each sub-period.

[0007] In one embodiment, the process of obtaining the deviation change characteristic value is as follows: By analyzing the correlation between the k-th type of monitoring data in phase j and each of the other monitoring data in each sub-period, the deviation change correlation factor of the k-th type of monitoring data in phase j is obtained in each sub-period. Calculate the sum of the correlation value of the change in the k-th monitoring data of the j-th phase and the correlation factor of the deviation change in each sub-period; Calculate the range of the fitted curve corresponding to the k-th type of monitoring data in phase j at each time point within each sub-time period; The characteristic value of the deviation change of the k-th monitoring data of the j-th phase in each sub-period is directly proportional to the range and inversely proportional to the sum.

[0008] In one embodiment, the process of obtaining the deviation change correlation factor is as follows: Within each sub-period of the k-th monitoring data in phase j, calculate the absolute value of the temporal correlation coefficient between the k-th monitoring data in phase j and each of the other monitoring data. Use the mean of the absolute values ​​of the correlation coefficients between the k-th monitoring data in phase j and all the other monitoring data as the deviation change correlation factor of the k-th monitoring data in phase j within each sub-period.

[0009] In one embodiment, the process of obtaining the dynamically changing feature value is as follows: Calculate the difference in the deviation change characteristic value of the k-th monitoring data between phase j and each of the other phases in all sub-time periods. Take the average of the difference between phase j and all the other phases of the k-th monitoring data at the key node as the dynamic change characteristic value of the k-th monitoring data of phase j at each time.

[0010] In one embodiment, the process of obtaining the dynamic change factor is as follows: Based on the deviation change characteristic value of the k-th monitoring data of phase j in all sub-time periods, the predicted value of the deviation change characteristic value of the k-th monitoring data of phase j after each time point is obtained. The product of the dynamic change characteristic value of the k-th type of monitoring data in phase j at each time point and the predicted value is used as the dynamic change factor of the k-th type of monitoring data in phase j at each time point.

[0011] In one embodiment, the process of obtaining the influence weight is as follows: Obtain the normalized value of the dynamic change factor of the kth type of monitoring data of each phase at each time point, wherein the sum of the normalized values ​​of the dynamic change factor of the kth type of monitoring data of all phases of each key node at each time point is 1. The mean of the normalized values ​​of the dynamic change factors of all types of monitoring data for each phase at each time point is used as the influence weight of each phase at each time point.

[0012] In one embodiment, the process of obtaining the voltage characteristic value is as follows: The weighted sum of the differences between the voltage data of all phases of each critical node at each time point and their rated values ​​is used as the voltage characteristic value of each critical node at each time point. The weight of the difference between the voltage data of each phase and its rated value is the influence weight of each phase.

[0013] Secondly, embodiments of this application also provide a fast voltage compensation device for distribution radio stations based on controllable series compensation, wherein the device contains: The data monitoring unit is used to collect various monitoring data of each phase of each key node in the distribution transformer area in real time; The main control unit is used to obtain the sub-periods of various monitoring data of each phase by the difference distribution between various monitoring data of each phase and their rated values; by the correlation between the changes of various monitoring data of each phase and each other phase of the key node in each sub-period, it obtains the change correlation value of various monitoring data of each phase in each sub-period; and by combining the correlation between various monitoring data of each phase and each other monitoring data in each sub-period, as well as the difference between various monitoring data of each phase and their rated values ​​in each sub-period, it obtains the deviation change characteristic value of various monitoring data of each phase in each sub-period. By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases of its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time are obtained. Then, the influence weight of each phase of each key node at each time is obtained. Finally, combined with the difference between the voltage data of each phase of each key node at each time and its rated value, the voltage characteristic value of each key node at each time is obtained, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

[0014] This application has at least the following beneficial effects: This application utilizes the difference distribution between various monitoring data and their rated values ​​to divide the collection period of various monitoring data into sub-periods, enabling the capture of the instantaneous dynamic changes in various monitoring data. The division of sub-periods can dynamically adapt to seasonal load and line impedance changes, improving the adaptability of monitoring and compensation. By calculating the change correlation value, the differences in changes of various monitoring data of each phase under dynamic conditions can be assessed, thereby identifying three-phase imbalance and providing a basis for subsequent compensation strategies. Furthermore, by combining the correlation between monitoring data and the deviation of monitoring data from rated values, the deviation change characteristic value is calculated, which can more comprehensively assess the deviation change characteristics of various monitoring data of each phase and provide a more accurate basis for adjusting the firing angle. Furthermore, by comprehensively comparing the change characteristics of each phase and the other phases under load impact at different time stages, significant dynamic changes in various monitoring data of each phase under dynamic load changes can be identified. Then, by predicting the characteristic value of deviation change, the future change trend of various monitoring data of each phase can be predicted in advance, providing forward-looking guidance for compensation strategies. In addition, the impact of each phase on voltage compensation can be quantified. By comprehensively considering the impact of each phase on voltage compensation at each key node, the voltage deviation of each key node can be evaluated, and the firing angle in the voltage compensation process can be accurately determined, so that the adjustment of the firing angle matches the load characteristics, thereby improving the accuracy of voltage compensation in the distribution substation area. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a method for rapid voltage compensation in a distribution station area based on controllable series compensation, provided in one embodiment of this application. Figure 2 This is a schematic diagram illustrating the process of obtaining voltage characteristic values; Figure 3 This is a schematic diagram illustrating the process of determining the trigger angle. Detailed Implementation

[0017] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It should be understood that, unless otherwise stated, " / " in this application means "or".

[0019] It should also be noted that the terms "first" and "second" in this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0020] The following description, in conjunction with the accompanying drawings, details the specific scheme of the controllable series compensation-based distribution area voltage fast compensation device and compensation method provided in this application.

[0021] One embodiment of this application provides a distribution area voltage fast compensation device based on controllable series compensation, comprising: a thyristor controlled series capacitor (TCSC) unit, a data monitoring unit, a main control unit, a bypass protection unit, and a power supply unit; The TCSC unit consists of a fixed capacitor bank, a thyristor valve bank, and a parallel reactor. By adjusting the thyristor firing angle, the equivalent capacitive reactance is changed, thereby achieving dynamic compensation of the line impedance. The data monitoring unit uses sensors to collect monitoring data, specifically: real-time collection of various monitoring data for each phase of each key node in the distribution transformer area; The main control unit analyzes monitoring data and outputs control commands in real time through a built-in data preprocessing algorithm and trigger angle optimization model. Specifically, it obtains the sub-time periods of various monitoring data of each phase by the difference distribution between various monitoring data of each phase and their rated values; it obtains the change correlation value of various monitoring data of each phase in each sub-time period by the correlation between various monitoring data of each phase and the other phases of the key node in each sub-time period; and it obtains the deviation change characteristic value of various monitoring data of each phase in each sub-time period by combining the correlation between various monitoring data of each phase and each other monitoring data in each sub-time period, as well as the difference between various monitoring data of each phase and their rated values ​​in each sub-time period. By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases of its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time are obtained. Then, the influence weight of each phase of each key node at each time is obtained. Finally, combined with the difference between the voltage data of each phase of each key node at each time and its rated value, the voltage characteristic value of each key node at each time is obtained. The voltage of the distribution substation is compensated based on the controllable series compensation technology. The bypass protection unit consists of a fast thyristor and an overcurrent protector. When the compensation device fails or the line is short-circuited, the TCSC unit is isolated from the line, thereby ensuring the continuity of power supply. The power supply unit provides a stable power supply to the TCSC unit, data monitoring unit, main control unit, and bypass protection unit.

[0022] Please see Figure 1The diagram illustrates a flowchart of a method for rapid voltage compensation in a distribution station area based on controllable series compensation, according to an embodiment of this application. The method includes the following steps: Step 1: Collect various monitoring data of each phase of each key node in the distribution radio area in real time.

[0023] During the operation of the distribution transformer substation, various monitoring data are collected in real time. Specifically, monitoring data is collected at key nodes in the substation, including the beginning and end of the substation lines, the nodes before and after the TCSC unit access point, and load concentration points, such as the output node of the motor distribution box. The monitoring data includes voltage, current, and temperature data. At each key node, voltage, current, and temperature sensors are used to collect voltage, current, and temperature data for each phase of each key node. The collected monitoring data is then transmitted to the main control unit via optical fiber.

[0024] In this embodiment, the acquisition frequency of voltage data, current data and temperature data is 20kHz. The acquisition frequency value is preset by the user and the implementer can set it according to the actual situation. This application does not impose any special restrictions.

[0025] The main control unit preprocesses the received monitoring data to reduce the interference of environmental noise and instrument noise on the monitoring data.

[0026] In this embodiment, a wavelet transform-based denoising algorithm is used to denoise the acquired voltage and current data respectively, reducing the impact of high-frequency interference on the monitoring data by separating transient disturbance signals and steady-state signals; a mean filter is used to smooth the acquired temperature data, reducing the impact of temperature anomalies caused by environmental noise and instrument noise on the accuracy of temperature monitoring; the wavelet transform-based denoising algorithm and the mean filter are well-known technologies and will not be described in detail in this application. As other implementation methods, based on the ability to denoise the acquired voltage, current, and temperature data, implementers may use other existing feasible technologies, and this application does not impose any special restrictions.

[0027] Furthermore, the various monitoring data after preprocessing are standardized to avoid the impact of different units on the subsequent analysis of the dynamic change characteristics during operation.

[0028] In this embodiment, taking voltage data as an example, the process of standardizing voltage data is as follows: the maximum value in the collected voltage data is statistically analyzed, and the ratio of each voltage data to the maximum value is calculated. As another implementation method, based on the ability to standardize voltage data, current data and temperature data, the implementer may adopt other existing feasible technologies, such as the Min-Max normalization method, etc. This application does not impose any special restrictions.

[0029] Step 2: Obtain the sub-time periods of various monitoring data for each phase; obtain the correlation values ​​and deviation characteristics of the various monitoring data for each phase within each sub-time period; then obtain the dynamic change characteristics and dynamic change factors of various monitoring data for each phase at each time point; then obtain the influence weight of each phase of each key node at each time point; and finally, combine the voltage data of each phase of each key node at each time point with the difference between its rated value and the voltage characteristic value of each key node at each time point, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

[0030] In the process of rapid voltage compensation of distribution substations based on controllable series compensation, the dynamic changes in the load of the distribution substation lead to problems such as three-phase load asymmetry and dynamic parameter coupling. Specifically, the load of the distribution substation is mostly connected in a mixed manner of single-phase and three-phase, which causes inconsistent changes in the parameters of the three phases during operation, resulting in dynamic fluctuations in line impedance and load power, which leads to a large deviation in voltage compensation of the distribution substation and reduces the accuracy of rapid voltage compensation of the distribution substation.

[0031] Based on the above analysis, this application fully considers the dynamic change characteristics of monitoring data during the operation of the distribution substation, accurately analyzes the actual voltage compensation deviation characteristics, and then dynamically adjusts the firing angle to improve the accuracy of voltage compensation for the distribution substation based on controllable series compensation. The specific analysis and processing steps are as follows: Step 2.1: Obtain the sub-periods of the monitoring data of each phase by the difference distribution between the various monitoring data of each phase and their rated values; obtain the change correlation value of the various monitoring data of each phase in each sub-period by the correlation between the various monitoring data of each phase and the other phases of the key node in each sub-period; and obtain the deviation change characteristic value of the various monitoring data of each phase in each sub-period by combining the correlation between the various monitoring data of each phase and each other monitoring data in each sub-period, as well as the difference between the various monitoring data of each phase and their rated values ​​in each sub-period.

[0032] Based on the preprocessed monitoring data from the main control unit, the differences in three-phase dynamic changes during operation monitoring are analyzed to accurately extract the characteristics of three-phase change differences affected by the dynamic fluctuations of the distribution substation load. Specifically, taking the k-th type of monitoring data of the j-th phase at the i-th key node as an example, the deviation response times of the k-th type of monitoring data of the j-th phase at the i-th key node are obtained by analyzing the difference distribution between the k-th type of monitoring data of the j-th phase at the i-th key node and its rated value. The specific process is as follows: Calculate the difference between the k-th monitoring data and its rated value at each time point. Arrange the differences between the k-th monitoring data and its rated value in the local time period before each time point according to the time sequence and perform curve fitting. Use the fitted curve as the deviation change curve of the k-th monitoring data at each time point to reflect the time sequence dynamic change characteristics of the k-th monitoring data during the operation of the distribution area. During the operation of the distribution substation, due to differences in load access methods and the time-series dynamic changes of the three-phase load, the dynamic change trend of the k-th monitoring data differs significantly from its rated value, and the load impact characteristics also differ significantly. Therefore, the extreme points in the deviation change curve of the k-th monitoring data of the j-th phase at each time point are taken as the deviation response times of the k-th monitoring data of the j-th phase at each time point, that is, the key time points of the response of the k-th monitoring data of the j-th phase under the load impact characteristics.

[0033] In this embodiment, the local time period before each moment refers to the time interval for collecting monitoring data before each moment.

[0034] In this embodiment, the least squares method is used to perform curve fitting on the difference between the monitoring data and its rated value. The least squares method is a well-known technique and will not be described in detail in this application. As other implementation methods, based on the ability to perform curve fitting on the difference between the monitoring data and its rated value, the implementer may use other existing techniques, such as local weighted regression, K-nearest neighbor regression, etc. This application does not impose any special restrictions.

[0035] In this embodiment, an extreme point detection algorithm is used to obtain each extreme point in the deviation change curve. The extreme point detection algorithm is a well-known technology and will not be described in detail in this application. As other implementation methods, based on the ability to obtain each extreme point in the deviation change curve, implementers may use other existing technologies, such as peak and trough detection algorithms, automatic multi-scale peak search algorithms, etc. This application does not impose any special restrictions.

[0036] To further analyze the response characteristics of monitoring data under load impact characteristics in different time periods, the deviation response times of the k-th monitoring data of phase j at each time point are used as the dividing points. The local time periods before each time point are divided into sub-time periods of the k-th monitoring data of phase j. The difference between the k-th monitoring data at each time point and its adjacent time point is recorded as the change value of the k-th monitoring data at each time point. Furthermore, within each sub-time period of the k-th monitoring data of phase j, the absolute value of the correlation coefficient between phase j and each of the other phases is calculated for the change value of the k-th monitoring data at all times. The mean of the absolute values ​​of the correlation coefficients between phase j and all other phases at the i-th key node is used as the change correlation value of the k-th monitoring data of phase j within each sub-time period. The smaller the calculated change correlation value, the greater the difference between the dynamic instantaneous change of the k-th monitoring data of phase j and the dynamic instantaneous change of the k-th monitoring data of the other phases under load impact, that is, the more significant the difference in the three-phase imbalance change under load impact.

[0037] In this embodiment, when calculating the change value of the kth type of monitoring data, the adjacent time points involved are the adjacent previous time points of each time point.

[0038] Furthermore, load shocks can cause changes in three-phase parameters. If the coordinated changes in the parameters of a single phase differ, the likelihood of differences in the dynamic fluctuations of single-phase parameters due to the load shock is greater. Based on the above analysis, within each sub-period of the k-th monitoring data of phase j, the absolute value of the temporal correlation coefficient between the k-th monitoring data of phase j and each of the other monitoring data is calculated. The mean of the absolute values ​​of the correlation coefficients between the k-th monitoring data of phase j and all other monitoring data is used as the deviation change correlation factor of the k-th monitoring data of phase j within each sub-period. The smaller the calculated deviation change correlation factor, the less correlated the changes of the k-th monitoring data of phase j with the other monitoring data are under the influence of the load shock.

[0039] In this embodiment, the correlation coefficients between the changed values ​​and between the monitoring data are both Pearson correlation coefficients. The calculation of the Pearson correlation coefficient is a well-known technique and will not be described in detail here. As other implementation methods, based on the ability to measure the correlation between the changed values ​​and between the monitoring data, the implementer may use other existing techniques, such as Spearman correlation coefficient, etc. This application does not impose any special restrictions.

[0040] Furthermore, by combining the correlation values ​​and deviation change correlation factors of the k-th monitoring data of phase j in each sub-period, and the difference distribution between the k-th monitoring data of phase j and its rated value in each sub-period, the deviation change characteristic values ​​of the k-th monitoring data of phase j in each sub-period are obtained, specifically: Calculate the sum of the correlation value of the change in the k-th monitoring data of the j-th phase and the correlation factor of the deviation change in each sub-period; Calculate the range of the deviation change curve of the k-th monitoring data of the j-th phase at each time point in each sub-period; the range reflects the deviation change of the k-th monitoring data, and the larger the deviation change, the more severe the load impact in each sub-period; The characteristic value of the deviation change of the k-th monitoring data of the j-th phase in each sub-period is directly proportional to the range and inversely proportional to the sum.

[0041] In this embodiment, the sum of the sum and the cumulative value of the values ​​greater than 0 are calculated. The ratio of the range to the cumulative value is used as the deviation change characteristic value of the k-th monitoring data of the j-th phase in each sub-period. The values ​​greater than 0 are used to avoid the denominator being 0. The specific value of the values ​​greater than 0 is preset by the user. The implementer can set it according to the actual situation. In this embodiment, the specific value of the values ​​greater than 0 is 0.001.

[0042] It should be noted that the larger the calculated deviation change characteristic value, the more severe the load impact response of the k-th monitoring data of phase j in each sub-period.

[0043] Based on the method for obtaining the deviation change characteristic value of the k-th type of monitoring data of phase j in each sub-period, the deviation change characteristic value of various monitoring data of each phase of each key node in each sub-period is obtained.

[0044] Step 2.2: By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases at its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time point are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time point are obtained.

[0045] Based on the above analysis, and further combined with the time-series change characteristics of the load impact response of a single phase during the operation of the distribution substation, the change characteristics of a single phase and the other phases under load impact are compared and analyzed. Based on the analysis results, the dynamic change difference of a single phase is extracted. The dynamic change difference refers to the difference between the change characteristics of the monitoring data of a single phase under dynamic conditions and those of the other phases. In this way, the difference in the operating characteristics of a single phase under dynamic load changes and line impedance changes can be accurately determined.

[0046] Based on the above analysis, the difference in the deviation change characteristic value of the k-th monitoring data between phase j and each of the other phases is calculated in all sub-time periods. The average of the difference between phase j and all other phases of the k-th monitoring data at the i-th key node is taken as the dynamic change characteristic value of the k-th monitoring data of phase j at each time point. The larger the calculated dynamic change characteristic value, the more significant the difference in the dynamic change of the k-th monitoring data of phase j under the influence of dynamic load changes.

[0047] In this embodiment, the calculation process for the difference in the deviation change characteristic value of the k-th monitoring data between the j-th phase and each of the other phases in all sub-time periods is as follows: the deviation change characteristic values ​​of the k-th monitoring data of each phase in all sub-time periods are arranged in chronological order to form a sequence of deviation change characteristic values ​​of the k-th monitoring data of each phase. The DTW (Dynamic Time Warping) distance of the deviation change characteristic value sequence of the k-th monitoring data between the j-th phase and each of the other phases is calculated. The DTW distance is a well-known technology and will not be described in detail in this application. As other implementation methods, based on the ability to measure the degree of difference between the deviation change characteristic value sequences, the implementer may adopt other existing technologies, such as Euclidean distance, etc. This application does not impose any special restrictions.

[0048] Furthermore, in order to accurately reflect the differences in single-phase dynamic changes under the influence of dynamic load changes during the operation of the distribution substation, a time series prediction algorithm is used to obtain the predicted values ​​of the deviation change characteristics of the k-th monitoring data of each phase after each time point, based on the deviation change characteristic value sequence of the k-th monitoring data of each phase.

[0049] In this embodiment, the exponential moving average method is used to obtain the predicted value of the deviation change characteristic value. The process of using the exponential moving average method for prediction and evaluation is a well-known technology and will not be described in detail here. As other implementation methods, based on the ability to obtain the predicted value of the deviation change characteristic value, the implementer may select other existing feasible technologies, and this application does not impose any special restrictions.

[0050] Furthermore, by using the dynamic change characteristic value of the k-th type of monitoring data in phase j at each time point, and the predicted value of the deviation change characteristic value of the k-th type of monitoring data in phase j after each time point, the dynamic change factor of the k-th type of monitoring data in phase j at each time point is obtained, and the expression is: In the formula, This represents the dynamic change factor of the k-th type of monitoring data in the j-th phase at each time point; This represents the dynamic change characteristic value of the k-th type of monitoring data in the j-th phase at each time point; This represents the predicted value of the characteristic value of the deviation change of the k-th type of monitoring data in phase j after each time point.

[0051] It should be noted that the larger the calculated dynamic change factor, the more significant the difference in dynamic change of the k-th monitoring data of the j-th phase at different stages is obtained. Under the influence of the impact load at each moment, the dynamic change difference of the k-th monitoring data of the j-th phase is more significant, which has a greater impact on the analysis of the controllable series compensation process.

[0052] According to the method for obtaining the dynamic change factor of the k-th type of monitoring data of the j-th phase at each time point, the dynamic change factors of various monitoring data of each phase of each key node at each time point are obtained.

[0053] Step 2.3: Obtain the influence weight of each phase of each key node at each time point, and then combine the voltage data of each phase of each key node at each time point with the difference between its rated value and the voltage characteristic value of each key node at each time point, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

[0054] Based on the above analysis, the voltage deviation of each phase is evaluated by comprehensively considering the dynamic changes of various monitoring data of each phase during actual operation. Specifically, the dynamic change factor of the k-th type of monitoring data of all phases at each critical node at each time point is used as input. The normalized value of the dynamic change factor of the k-th type of monitoring data of each phase is output by the Softmax function and used as the characteristic coefficient of the k-th type of monitoring data of each phase at each time point. The characteristic coefficients of various monitoring data of each phase at each time point are obtained according to the method for obtaining the characteristic coefficients of the k-th type of monitoring data of each phase at each time point. The mean of the characteristic coefficients of all types of monitoring data of each phase at each time point is used as the influence weight of each phase at each time point. The Softmax function is a well-known technology and will not be described in detail in this application.

[0055] Furthermore, by combining the differences between the voltage data of each phase of each key node at each time point and their rated values, and the influence weights of each phase of each key node at each time point, the voltage characteristic values ​​of each key node at each time point are obtained, expressed as follows: In the formula, This represents the voltage characteristic value of the i-th critical node at each time step; This represents the total number of phases at the i-th critical node; This represents the difference between the voltage data of the j-th phase at the i-th critical node at each time point and its rated value. This represents the influence weight of the j-th phase of the i-th key node at each time point.

[0056] It should be noted that the larger the calculated voltage characteristic value, the greater the voltage deviation of the i-th critical node in the distribution substation under the influence of dynamic fluctuations, and the greater the impact of load surges on the line inductive reactance during voltage compensation. A schematic diagram of the voltage characteristic value acquisition process is shown below. Figure 2 As shown.

[0057] Step 2.4: Determine the firing angle in the voltage compensation process based on controllable series compensation by using the voltage characteristic values ​​of each key node at each time point.

[0058] Based on the above analysis, the firing angle in the voltage compensation process based on controllable series compensation is determined using voltage characteristic values; specifically, if the actual voltage under the influence of dynamic load impact is lower than the rated value, If the voltage is negative, capacitive reactive power needs to be injected to boost the voltage; if the actual voltage under the influence of dynamic load impact is higher than the rated value, If positive, capacitive reactive power needs to be absorbed to reduce voltage; the obtained voltage characteristic value is used as input, and the PI controller is used to obtain the target reactive power command for voltage compensation at each time. The target reactive power command indicates the amount of reactive power that the TCSC needs to inject into or absorb from the grid when correcting the voltage deviation at each time.

[0059] Furthermore, the target reactive power command is converted into a firing angle command executable by the TCSC. Specifically, firstly, based on the collected voltage data, the target equivalent capacitive reactance required to achieve the firing angle command is derived by using the correlation formula between reactive power and equivalent capacitive reactance. Then, based on the topology characteristics of the TCSC, the equivalent capacitive reactance and the thyristor firing angle are used for inverse solving to obtain the target firing angle that enables the equivalent capacitive reactance to reach the target value. The specific process of determining the firing angle based on the voltage deviation in the TCSC is well known to those skilled in the art and will not be elaborated here. A schematic diagram of the firing angle determination process is shown below. Figure 3 As shown.

[0060] Step 3: Perform rapid voltage compensation during the operation of the distribution transformer area based on controllable series compensation technology.

[0061] Based on the analysis in step 2, the controllable series compensation technology is used to achieve rapid voltage compensation during the operation of the distribution substation. The specific process is as follows: (1) First, the TCSC state is switched based on the determined firing angle. Specifically, the optimized firing angle command is converted into a thyristor firing pulse signal by the main control unit. The thyristor firing pulse signal is transmitted to the TCSC thyristor valve group and the command is sent to the switching switch to switch the TCSC from the standby state to the working state. During the switching process, the fixed capacitor bank is connected to the line first, and then the thyristor is turned on and off periodically according to the firing angle. The current of the parallel reactor is changed by the determined conduction angle, thereby adjusting the equivalent capacitive reactance of the TCSC to stabilize the equivalent capacitive reactance at the target value. It should be noted that the entire switching process should be kept <20ms to avoid instantaneous fluctuations in the line voltage.

[0062] (2) Secondly, real-time compensation and voltage stability control are achieved through TCSC; specifically, after TCSC is connected to the line, capacitive reactance compensation is performed on the distribution line in series, and the line inductive reactance is offset by capacitive reactance compensation; for example, when a cluster motor starts in the distribution area, the current of the distribution line will increase and the voltage will drop. The line inductive reactance of the distribution area can be compensated by the equivalent capacitive reactance of TCSC, thereby reducing the voltage drop of the distribution line impedance and compensating the voltage on the load side of the distribution area to the rated value.

[0063] (3) After the compensation is completed, the distribution area voltage fast compensation device based on controllable series compensation will be switched to standby mode; specifically, when the load recovers to stability and the voltage deviation rate changes within If the compensation requirement ends within the specified range and the duration is greater than 10 seconds, the main control unit will switch the TCSC to standby mode. At the same time, the bypass protection unit will continuously monitor the system. If the TCSC device temperature is too high or the line is faulty, the bypass protection unit will immediately trigger the bypass circuit and isolate the TCSC from the line by conducting the fast thyristor. After the fault is repaired, the switching switch will be closed to restore the normal power supply to the line.

[0064] In summary, this application, by analyzing the differences between various monitoring data and their rated values, divides the collection periods of various monitoring data into sub-periods, enabling the capture of the instantaneous dynamic changes in various monitoring data. The division of sub-periods can dynamically adapt to seasonal load and line impedance changes, improving the adaptability of monitoring and compensation. By calculating the correlation values, the differences in the changes of various monitoring data for each phase under dynamic conditions can be assessed, thereby identifying three-phase imbalance and providing a basis for subsequent compensation strategies. Furthermore, by combining the correlation between monitoring data and the deviation of the monitoring data from the rated values, the deviation change characteristic value is calculated, enabling a more comprehensive assessment of the deviation change characteristics of various monitoring data for each phase, providing a more accurate basis for adjusting the firing angle. Furthermore, by comprehensively comparing the change characteristics of each phase and the other phases under load impact at different time stages, significant dynamic changes in various monitoring data of each phase under dynamic load changes can be identified. Then, by predicting the characteristic value of deviation change, the future change trend of various monitoring data of each phase can be predicted in advance, providing forward-looking guidance for compensation strategies. In addition, the impact of each phase on voltage compensation can be quantified. By comprehensively considering the impact of each phase on voltage compensation at each key node, the voltage deviation of each key node can be evaluated, and the firing angle in the voltage compensation process can be accurately determined, so that the adjustment of the firing angle matches the load characteristics, thereby improving the accuracy of voltage compensation in the distribution substation area.

[0065] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0066] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from its essential characteristics. Therefore, the embodiments described above should be considered exemplary and non-limiting in all respects.

Claims

1. A method for rapid voltage compensation in distribution radio stations based on controllable series compensation, characterized in that, The method includes the following steps: Real-time acquisition of various monitoring data for each phase of each key node in the distribution radio area; By analyzing the differences between various monitoring data of each phase and their rated values, we obtain the sub-periods of various monitoring data of each phase. By analyzing the correlation between the changes of various monitoring data of each phase and each other phase of the key node in each sub-period, we obtain the correlation values ​​of the changes of various monitoring data of each phase in each sub-period. In addition, by combining the correlation between various monitoring data of each phase and each other monitoring data in each sub-period, as well as the differences between various monitoring data of each phase and their rated values ​​in each sub-period, we obtain the characteristic values ​​of the deviation changes of various monitoring data of each phase in each sub-period. By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases of its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time are obtained. Then, the influence weight of each phase of each key node at each time is obtained. Finally, combined with the difference between the voltage data of each phase of each key node at each time and its rated value, the voltage characteristic value of each key node at each time is obtained, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

2. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 1, characterized in that, The process of obtaining the sub-time period is as follows: Calculate the difference between various monitoring data and their rated values ​​at each time point. Arrange the difference between the k-th monitoring data of phase j and its rated value in the local time period before each time point according to time sequence and perform curve fitting. Take the time of each extreme point in the fitted curve as the dividing point and divide the local time period before each time point into sub-time periods of the k-th monitoring data of phase j.

3. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 2, characterized in that, The process for obtaining the change-related value is as follows: The differences between various monitoring data at each time point and its adjacent time points are recorded as the changes in various monitoring data at each time point; Within each sub-period of the k-th monitoring data in phase j, calculate the absolute value of the correlation coefficient between phase j and each of the other phases for the change value of the k-th monitoring data at all times. Take the mean of the absolute values ​​of the correlation coefficients between phase j and all other phases of the key node as the change correlation value of the k-th monitoring data in phase j within each sub-period.

4. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 2, characterized in that, The process for obtaining the characteristic value of the deviation change is as follows: By analyzing the correlation between the k-th type of monitoring data in phase j and each of the other monitoring data in each sub-period, the deviation change correlation factor of the k-th type of monitoring data in phase j is obtained in each sub-period. Calculate the sum of the correlation value of the change in the k-th monitoring data of the j-th phase and the correlation factor of the deviation change in each sub-period; Calculate the range of the fitted curve corresponding to the k-th type of monitoring data in phase j at each time point within each sub-time period; The characteristic value of the deviation change of the k-th monitoring data of the j-th phase in each sub-period is directly proportional to the range and inversely proportional to the sum.

5. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 4, characterized in that, The process for obtaining the correlation factor of the deviation change is as follows: Within each sub-period of the k-th monitoring data in phase j, calculate the absolute value of the temporal correlation coefficient between the k-th monitoring data in phase j and each of the other monitoring data. Use the mean of the absolute values ​​of the correlation coefficients between the k-th monitoring data in phase j and all the other monitoring data as the deviation change correlation factor of the k-th monitoring data in phase j within each sub-period.

6. The method for rapid voltage compensation of distribution radio stations based on controllable series compensation as described in claim 2, characterized in that, The process for obtaining the dynamically changing feature values ​​is as follows: Calculate the difference in the deviation change characteristic value of the k-th monitoring data between phase j and each of the other phases in all sub-time periods. Take the average of the difference between phase j and all the other phases of the k-th monitoring data at the key node as the dynamic change characteristic value of the k-th monitoring data of phase j at each time.

7. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 2, characterized in that, The process of obtaining the dynamic change factor is as follows: Based on the deviation change characteristic value of the k-th monitoring data of phase j in all sub-time periods, the predicted value of the deviation change characteristic value of the k-th monitoring data of phase j after each time point is obtained. The product of the dynamic change characteristic value of the k-th type of monitoring data in phase j at each time point and the predicted value is used as the dynamic change factor of the k-th type of monitoring data in phase j at each time point.

8. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 2, characterized in that, The process of obtaining the influence weights is as follows: Obtain the normalized value of the dynamic change factor of the kth type of monitoring data of each phase at each time point, wherein the sum of the normalized values ​​of the dynamic change factor of the kth type of monitoring data of all phases of each key node at each time point is 1. The mean of the normalized values ​​of the dynamic change factors of all types of monitoring data for each phase at each time point is used as the influence weight of each phase at each time point.

9. The method for rapid voltage compensation of distribution station areas based on controllable series compensation as described in claim 1, characterized in that, The process for obtaining the voltage characteristic value is as follows: The weighted sum of the differences between the voltage data of all phases of each critical node at each time point and their rated values ​​is used as the voltage characteristic value of each critical node at each time point. The weight of the difference between the voltage data of each phase and its rated value is the influence weight of each phase.

10. A distribution station area voltage fast compensation device based on controllable series compensation, employing the distribution station area voltage fast compensation method based on controllable series compensation as described in claim 1, characterized in that... The device contains: The data monitoring unit is used to collect various monitoring data of each phase of each key node in the distribution transformer area in real time; The main control unit is used to obtain the sub-periods of various monitoring data of each phase by the difference distribution between various monitoring data of each phase and their rated values; by the correlation between the changes of various monitoring data of each phase and each other phase of the key node in each sub-period, it obtains the change correlation value of various monitoring data of each phase in each sub-period; and by combining the correlation between various monitoring data of each phase and each other monitoring data in each sub-period, as well as the difference between various monitoring data of each phase and their rated values ​​in each sub-period, it obtains the deviation change characteristic value of various monitoring data of each phase in each sub-period. By comparing the deviation change characteristic values ​​of various monitoring data between each phase and the other phases of its key node, the dynamic change characteristic values ​​of various monitoring data of each phase at each time are obtained. Combined with the predicted values ​​of the deviation change characteristic values ​​of various monitoring data of each phase, the dynamic change factors of various monitoring data of each phase at each time are obtained. Then, the influence weight of each phase of each key node at each time is obtained. Finally, combined with the difference between the voltage data of each phase of each key node at each time and its rated value, the voltage characteristic value of each key node at each time is obtained, so as to compensate the voltage of the distribution transformer area based on the controllable series compensation technology.

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