A closed-loop adaptive control method and system for voltage compensation of a power distribution line

Abstract

The application relates to the technical field of voltage compensation control, in particular to a closed-loop adaptive control method and system for voltage compensation of a power distribution line, which comprises the following steps: collecting voltage, current and voltage error signals of a target power distribution line; calculating line impedance and average line load rate according to voltage and current in a sliding window; analyzing the change trend of impedance and load rate, and quantifying an impedance-load coupling influence coefficient; analyzing the oscillation frequency and amplitude of the voltage error, constructing a relative oscillation coefficient, combining the coupling influence coefficient to determine a parameter adjustment coefficient; and adjusting the proportional parameter of a PI controller in the next parameter adjustment period by using the parameter adjustment coefficient, so as to realize voltage control. The application solves the problem that a fixed parameter PI controller cannot simultaneously consider compensation accuracy and response speed under line working condition time variation, and improves the steady-state control accuracy and response speed of voltage compensation.

Description

Technical Field

[0001] This application relates to the field of voltage compensation control technology, specifically to a closed-loop adaptive control method and system for voltage compensation of power distribution lines. Background Technology

[0002] Distribution lines are a crucial component of power systems; however, their voltage quality is highly susceptible to disturbances from various external and internal factors, which can affect the operational stability of the power grid and the safety of electrical equipment. Therefore, existing technologies typically employ voltage compensation measures for distribution lines to maintain grid voltage stability and suppress voltage fluctuations.

[0003] Currently, Dynamic Voltage Restorers (DVRs) are widely used in distribution network voltage compensation due to their fast response, strong harmonic suppression capability, and high reliability, and often employ closed-loop control strategies based on PI controllers. However, the parameters of PI controllers are typically set to fixed values ​​based on rated operating conditions. Because actual distribution network operation exhibits significant time-varying characteristics, influenced by factors such as temperature, aging, and power consumption fluctuations, line impedance and load continuously change, directly affecting voltage stability. When actual operating conditions deviate from the set conditions, PI controllers with fixed parameters struggle to balance compensation accuracy and response speed. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a closed-loop adaptive control method and system for voltage compensation in power distribution lines. The specific technical solution adopted is as follows:

[0005] In a first aspect, embodiments of this application provide a closed-loop adaptive control method for power distribution line voltage compensation, the method comprising the following steps:

[0006] Collect various electrical parameter signals of the target power distribution line, including voltage signals, current signals, and voltage error signals;

[0007] Within the preset parameter adjustment period, a sliding time window is processed for each electrical parameter signal, and the impedance and average line load rate of the target power distribution line are calculated based on the current and voltage signals within each time window.

[0008] During any parameter adjustment period, the impedance-load coupling influence coefficient of the target distribution line is quantified by analyzing the changing trends of the target distribution line impedance and the average line load rate.

[0009] The oscillation frequency and amplitude of the voltage error signal within each time window are analyzed to determine the relative oscillation characteristic value, so as to construct the relative oscillation coefficient of the target distribution line within any parameter adjustment period. Combined with the impedance load coupling influence coefficient, the parameter adjustment coefficient within any parameter adjustment period is determined.

[0010] Using the parameter adjustment coefficient, the proportional parameter in the PI controller is adjusted within the next parameter adjustment period adjacent to any parameter adjustment period in order to control the voltage in the target power distribution line.

[0011] Preferably, the quantification process of the impedance load coupling influence coefficient is as follows:

[0012] During any parameter adjustment period, the trend term sequence of the target distribution line impedance and the trend term sequence of the average line load rate are extracted using the time series decomposition algorithm.

[0013] Fit all elements of the trend term sequence of impedance and all elements of the trend term sequence of average line load rate respectively, and normalize the slope of their respective fitted lines, which are denoted as the first trend value and the second trend value respectively.

[0014] Based on the first trend value and the second trend value, the impedance load coupling influence coefficient of the target power distribution line is determined within any parameter adjustment period.

[0015] Preferably, the impedance load coupling influence coefficient of the target power distribution line during any parameter adjustment period is the average of the first trend value and the second trend value.

[0016] Preferably, the process for determining the relative oscillation characteristic value is as follows:

[0017] Within any parameter adjustment period, calculate the normalized value of the zero-crossing rate of the voltage error signal in each time window, and record it as the relative oscillation frequency of the voltage error signal in each time window.

[0018] The peak-to-peak value of the voltage error signal within each time window is normalized and used as the relative oscillation amplitude of the voltage error signal within each time window.

[0019] Based on the relative oscillation frequency and the relative oscillation amplitude, the relative oscillation characteristic values ​​under each time window are determined.

[0020] Preferably, the relative oscillation characteristic values ​​under each time window are positively correlated with the relative oscillation amplitude and negatively correlated with the relative oscillation frequency.

[0021] Preferably, the process for constructing the relative oscillation coefficient of the target distribution line within the adjustment period of any parameter is as follows:

[0022] The relative oscillation characteristic values ​​under all time windows within any parameter adjustment period are used as input to the time series prediction algorithm. The predicted value of the relative oscillation characteristic value at the next time adjacent to the end of the parameter adjustment period is output as the relative oscillation coefficient of the target distribution line within any parameter adjustment period.

[0023] Preferably, the parameter adjustment coefficient within any parameter adjustment period is positively correlated with the impedance load coupling influence coefficient and the relative oscillation coefficient, respectively.

[0024] Preferably, the step of adjusting the proportional parameter in the PI controller within the next parameter adjustment period adjacent to any parameter adjustment period includes:

[0025] The optimized value of the proportional parameter in the PI controller during the next adjacent parameter adjustment period b. The expression is: In the formula, This represents the parameter adjustment coefficient during the parameter adjustment period b. , represents the preset additive factor and the preset multiplicative factor, respectively; round() represents the rounding function.

[0026] Preferably, controlling the voltage in the target power distribution line includes:

[0027] During the adjacent next parameter adjustment period, the voltage error at each moment is used as the input of the PI controller. The optimized value of the proportional parameter in the PI controller during the adjacent next parameter adjustment period is used as the proportional parameter in the PI controller, and a voltage control signal is output to compensate for the voltage at each moment. Secondly, embodiments of this application also provide a closed-loop adaptive control system for distribution line voltage compensation, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described closed-loop adaptive control methods for distribution line voltage compensation.

[0028] This application has at least the following beneficial effects:

[0029] This application constructs an impedance-load coupling influence coefficient by stripping away short-term fluctuation noise and extracting the long-term trend characteristics of impedance and load. This effectively overcomes the misleading effect of instantaneous interference on state assessment, accurately quantifies the degree of coupling influence of the synchronous evolution of impedance and load on the voltage drop in the subsequent target power distribution line, and provides a reliable macroscopic state basis for the forward-looking adaptive adjustment of the proportional parameters of the PI controller.

[0030] Furthermore, this application quantifies the oscillation characteristics of micro voltage error and predicts its future evolution trend, deeply integrates it with the coupling effect of macroscopic impedance load, constructs parameter adjustment coefficients, realizes a forward-looking global assessment of the system's dynamic response requirements, effectively avoids control oscillations caused by blindly adjusting parameters based solely on transient oscillations, and provides a reliable basis for the safe and accurate adaptive tuning of the PI controller's proportional parameters.

[0031] Ultimately, this application maps the parameter adjustment coefficient, which integrates macro-coupling trends and micro-oscillation predictions, to the safe and feasible domain of the proportional parameter for periodic forward control. This effectively avoids the slow response and control oscillations caused by blindly adjusting parameters in a fixed or single dimension, enabling the dynamic voltage restorer to match the dynamic evolution requirements of the circuit and improving the voltage compensation response speed and steady-state control accuracy. Attached Figure Description

[0032] 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.

[0033] Figure 1 A flowchart illustrating the steps of a closed-loop adaptive control method for voltage compensation of a power distribution line, provided in one embodiment of this application;

[0034] Figure 2 This is a schematic diagram of the proportional parameter adjustment process provided in one embodiment of this application. Detailed Implementation

[0035] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive objective, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a closed-loop adaptive control method and system for power distribution line voltage compensation proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0036] 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 pertains.

[0037] The following description, in conjunction with the accompanying drawings, details the specific scheme of the closed-loop adaptive control method and system for voltage compensation of power distribution lines provided in this application.

[0038] Please see Figure 1 The diagram illustrates a flowchart of a closed-loop adaptive control method for power distribution line voltage compensation according to an embodiment of this application. The method includes the following steps:

[0039] Step S1: Collect various electrical parameter signals of the target power distribution line, including voltage signals, current signals, and voltage error signals.

[0040] The process involves acquiring various electrical parameter signals of the target power distribution circuit, including current, voltage, and voltage error signals. The specific steps are as follows:

[0041] The voltage and current signals input to the dynamic voltage restorer of the target power distribution line are periodically collected, and the voltage error signal input to the PI controller of the dynamic voltage restorer is obtained using the same signal collection period. The sampling frequency of the voltage signal, current signal, and voltage error signal of the target power distribution line is consistent with the sampling frequency of the voltage in the dynamic voltage restorer. In this embodiment, the signal sampling frequency is set to 51.2kHz. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0042] Step S2: During the preset parameter adjustment period, a sliding time window is processed for each electrical parameter signal, and the impedance and average line load rate of the target distribution line are calculated based on the current and voltage signals in each time window.

[0043] Since the operating state of the target power distribution line is dynamically and continuously changing, if the electrical parameter signal is directly calculated as a whole during the entire parameter adjustment period, the resulting single average value will mask the dynamic evolution of the line impedance and load during that period and will not reflect its fluctuation pattern over time. Therefore, it is necessary to introduce a sliding time window to segment the signal during the parameter adjustment period, discretizing the macroscopic continuous change into local states under multiple microscopic time windows, so that the trend characteristics and local oscillation characteristics of its evolution over time can be extracted based on the local states of each time window in subsequent steps.

[0044] Specifically, in this embodiment, the voltage signal, current signal, and voltage error signal of the target power distribution line collected during the preset parameter adjustment period are segmented using sliding time window technology to obtain signal segments under each time window. In this embodiment, the length of any parameter adjustment period is 3 seconds, and the length and step size of the sliding time window are both set to 100 ms. In actual applications, as other implementation methods, implementers can also set them according to specific circumstances. This embodiment does not impose any special restrictions.

[0045] Furthermore, this embodiment calculates the impedance and average line load rate of the target distribution line based on the current and voltage signals within each time window. Specifically:

[0046] Within any parameter adjustment period, for the current and voltage signals under each time window, the fundamental component is extracted to obtain the effective value of the voltage power frequency, the effective value of the current power frequency, and the phase difference between the voltage fundamental phase and the current fundamental phase under the corresponding time window. The ratio of the effective value of the voltage power frequency to the effective value of the current power frequency under the same time window is used as the magnitude of the line impedance under that time window, and the phase difference is used as the line impedance angle under that time window to characterize the line impedance under that time window. Furthermore, the ratio of the magnitude of the line impedance under each time window to the characteristic impedance of the target distribution line is used as the normalized result of the impedance of the target distribution line under each time window to eliminate the influence of data dimensions between lines of different voltage levels.

[0047] Meanwhile, the ratio of the effective value of the current at power frequency to the rated current of the target distribution line under each time window is used as the average line load rate under each time window to evaluate the change of the load size of the target distribution line over time during the parameter adjustment period.

[0048] The calculation process for line impedance and line load rate is a well-known technique and will not be elaborated further.

[0049] Step S3: During any parameter adjustment period, the impedance-load coupling influence coefficient of the target distribution line is quantified by analyzing the changing trends of the target distribution line impedance and the average line load rate.

[0050] In power distribution lines, dynamic changes in line impedance and load directly affect the voltage drop level. When line impedance and load increase, the voltage drop increases, leading to a corresponding increase in the voltage error input to the PI controller of the dynamic voltage restorer. If the proportional parameter of the PI controller is too small, it will be unable to quickly inject sufficient compensation voltage due to insufficient dynamic response capability, causing continuous low-frequency large-amplitude oscillations in the line voltage. Conversely, when line impedance and load decrease, the voltage drop decreases, and the voltage error input to the PI controller decreases. If the proportional parameter of the PI controller is too large, it will inject excessive compensation voltage due to overly fast dynamic response, causing continuous high-frequency small-amplitude oscillations in the line voltage, affecting the compensation accuracy.

[0051] However, the effects of impedance and load on voltage drop are not isolated but rather coupled, and this effect depends primarily on their dynamic evolution over a period of time, rather than their static values ​​at a single moment. If only static values ​​are used for evaluation, it is highly susceptible to being misled by instantaneous interference noise, making it impossible to accurately predict the subsequent continuous trend of voltage drop changes. Therefore, it is necessary to isolate short-term fluctuation noise, extract the long-term trends of impedance and load over time, and quantify their coupling influence on voltage drop by analyzing the synchronous evolution characteristics of these trends. In this embodiment, within any parameter adjustment period, the impedance-load coupling influence coefficient of the target distribution line is quantified by analyzing the changing trends of the target distribution line impedance and the average line load rate. The specific process is as follows:

[0052] In this embodiment, during any parameter adjustment period, the trend sequence of the target distribution line impedance and the trend sequence of the average line load rate are extracted using a time series decomposition algorithm. The time series decomposition algorithm used in this embodiment is the STL time series decomposition algorithm. In practical applications, as other implementation methods, implementers may also use other time series decomposition algorithms according to specific circumstances. This embodiment does not impose any special restrictions.

[0053] Furthermore, fitting is performed on all elements of the trend term sequence of impedance and all elements of the trend term sequence of average line load rate, respectively. When fitting the trend term sequence of impedance, the time windows corresponding to all elements in the trend term sequence are numbered in chronological order, and the numbers are used as independent variables in the fitting algorithm. The values ​​corresponding to all elements are used as dependent variables in the fitting algorithm. The fitting process for all elements in the trend term sequence of average line load rate is the same as that for impedance, and will not be described in detail here. The slopes of their respective fitted lines are normalized and recorded as the first trend value and the second trend value, respectively.

[0054] It should be noted that there are many commonly used fitting algorithms. In this embodiment, the least squares method is used to fit all elements in the trend term sequence of impedance and all elements in the trend term sequence of average line load rate. In practical applications, as other implementation methods, implementers may also use other fitting algorithms according to specific circumstances. This embodiment does not impose any special restrictions.

[0055] It should be noted that in this embodiment, the slope is normalized using the tanh function to normalize it to the range of [0,1]. In practical applications, as other implementation methods, implementers may also choose other normalization methods such as the maximum and minimum value normalization method according to specific circumstances. This embodiment does not impose any special restrictions.

[0056] The process of extracting the trend term sequence using the STL time series decomposition algorithm, fitting the data using the least squares method, and normalizing the data using the tanh function are all well-known techniques and will not be elaborated further.

[0057] Furthermore, this embodiment determines the impedance load coupling influence coefficient of the target distribution line within any parameter adjustment period based on the first trend value and the second trend value. Specifically:

[0058] In this embodiment, the average of the first trend value and the second trend value within any parameter adjustment period is used as the impedance load coupling influence coefficient of the target power distribution line within any parameter adjustment period.

[0059] The impedance-load coupling influence coefficient characterizes the degree of coupling effect of macroscopic dynamic changes in impedance and load on the voltage drop of the target distribution line. It reflects the combined effect of the synchronous increase and decrease trends of the two in time evolution on the subsequent voltage drop depth. Since the slope is normalized by the tanh function in the calculation process, the physical dimensions of the original impedance (ohms) and load factor (percentage) have been eliminated. Therefore, the impedance-load coupling influence coefficient is a dimensionless parameter. The calculation of the impedance-load coupling influence coefficient is affected by the first trend value and the second trend value. When these two trend values ​​are larger, it indicates that the impedance and load increase more significantly in the current period. This reflects that the probability of the target distribution line generating a large voltage drop in the subsequent period is extremely high. The proportional parameter needs to be increased significantly to provide sufficient dynamic response capability and prevent low-frequency large-amplitude oscillations. Conversely, when these two trend values ​​are smaller, the impedance-load coupling influence coefficient is closer to 0. The voltage drop of the target distribution line will decrease. The proportional parameter needs to be reduced to prevent overreaction and high-frequency small-amplitude oscillations, thereby ensuring compensation accuracy.

[0060] Thus, this embodiment constructs an impedance-load coupling influence coefficient by stripping away short-term fluctuation noise and extracting the long-term trend characteristics of impedance and load. This effectively overcomes the misleading influence of instantaneous interference on state assessment, accurately quantifies the degree of coupling influence of the synchronous evolution of impedance and load on the voltage drop in the subsequent target power distribution line, and provides a reliable macroscopic state basis for the forward-looking adaptive adjustment of the proportional parameters of the PI controller.

[0061] Step S4: Analyze the oscillation frequency and amplitude of the voltage error signal within each time window, determine the relative oscillation characteristic value, construct the relative oscillation coefficient of the target distribution line within any parameter adjustment period, and combine it with the impedance load coupling influence coefficient to determine the parameter adjustment coefficient within any parameter adjustment period.

[0062] If the voltage error input to the PI controller of the dynamic voltage restorer exhibits low-frequency, large-amplitude oscillations, it indicates that the proportional parameter is too small, resulting in insufficient dynamic response. The proportional parameter should be increased to improve the voltage compensation response speed. Conversely, if the voltage error exhibits high-frequency, small-amplitude oscillations, it indicates that the proportional parameter is too large, resulting in an overly aggressive dynamic response. The proportional parameter should be decreased to improve the voltage compensation accuracy. However, the oscillation state of the voltage error is continuously evolving. Directly adjusting the parameters based solely on the current transient oscillation behavior can easily trigger control oscillations. Therefore, this embodiment analyzes the oscillation frequency and amplitude of the voltage error signal within each time window to determine the relative oscillation characteristic value, thereby constructing the relative oscillation coefficient of the target distribution line within any parameter adjustment period. Combined with the impedance load coupling influence coefficient, the parameter adjustment coefficient within any parameter adjustment period is determined to determine the final proportional parameter. The specific process is as follows:

[0063] First, this embodiment analyzes the oscillation frequency and amplitude of the voltage error signal within each time window to determine the relative oscillation characteristic value, thereby constructing the relative oscillation coefficient of the target distribution line within any parameter adjustment period. Specifically:

[0064] Within any parameter adjustment period, the normalized value of the zero-crossing rate of the voltage error signal in each time window is calculated and denoted as the relative oscillation frequency of the voltage error signal in each time window. In this embodiment, the maximum value is selected from the zero-crossing rates of the voltage error signal in all time windows within any parameter adjustment period, and the result of dividing the zero-crossing rate of the voltage error signal in each time window by the maximum value is used as the normalized value of the zero-crossing rate.

[0065] Furthermore, the peak-to-peak value of the voltage error signal within each time window is normalized and used as the relative oscillation amplitude of the voltage error signal within each time window. In this embodiment, the maximum value is selected from the peak-to-peak values ​​of the voltage error signal within all time windows during any parameter adjustment period, and the result of dividing the peak-to-peak value of the voltage error signal within each time window by the maximum value is used as the normalized result of the peak-to-peak value.

[0066] The extraction processes for zero-crossing rate and peak-to-peak value are well-known techniques and will not be elaborated further.

[0067] Furthermore, this embodiment determines the relative oscillation characteristic values ​​for each time window based on the relative oscillation frequency and the relative oscillation amplitude, specifically:

[0068] In this embodiment, the relative oscillation characteristic values ​​under each time window are positively correlated with the relative oscillation amplitude and negatively correlated with the relative oscillation frequency.

[0069] It should be understood that a positive correlation means that the dependent variable increases as the independent variable increases, and the dependent variable decreases as the independent variable decreases. The specific relationship can be additive or multiplicative, etc., and is determined by the actual application. This application does not impose any special restrictions. A negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. The relationship can be subtractive or divisive, etc., and is determined by the actual application.

[0070] Preferably, as an implementation method, in this embodiment, the difference between the relative oscillation amplitude and the relative oscillation frequency under each time window is normalized and used as the relative oscillation characteristic value under each time window.

[0071] It should be noted that in this embodiment, the maximum and minimum values ​​are selected from the differences between the relative oscillation amplitude and the relative oscillation frequency under all time windows within any parameter adjustment period, and are used as the maximum and minimum value parameters in the maximum and minimum value normalization method, respectively. In actual application, as other implementation methods, implementers may also adopt other normalization methods according to specific circumstances. This embodiment does not impose any special restrictions.

[0072] The process of normalizing data using the maximum-minimum normalization method is a well-known technique and will not be elaborated further.

[0073] Based on the relative oscillation characteristic value, it can be understood that the relative oscillation characteristic value is used to characterize the oscillation pattern of the voltage error signal within a single time window, reflecting whether the voltage error tends to oscillate at low frequency and large amplitude or at high frequency and small amplitude within that local period. Since the zero-crossing rate and peak-to-peak value are normalized by dividing by the historical maximum value during the calculation process, and then the difference is normalized by the maximum and minimum values, it is a dimensionless parameter. The calculation of the relative oscillation characteristic value is affected by both the relative oscillation amplitude and the relative oscillation frequency. When the relative oscillation amplitude is larger and the relative oscillation frequency is smaller, the relative oscillation characteristic value is larger. This reflects that the voltage error within the corresponding time window exhibits the characteristic of low-frequency, large-amplitude oscillation, indicating that the proportional parameter of the PI controller is set too small, resulting in insufficient dynamic response, and the proportional parameter needs to be increased to speed up the response. Conversely, when the relative oscillation amplitude is smaller and the relative oscillation frequency is larger, the relative oscillation characteristic value is smaller. This reflects that the voltage error within the corresponding time window exhibits the characteristic of high-frequency, small-amplitude oscillation, indicating that the proportional parameter of the PI controller is set too large, resulting in excessive dynamic response, and the proportional parameter needs to be reduced to suppress high-frequency fluctuations and ensure steady-state compensation accuracy.

[0074] Furthermore, in this embodiment, the relative oscillation characteristic values ​​under all time windows within any parameter adjustment period are used as input to the time series prediction algorithm, and the predicted value of the relative oscillation characteristic value at the next time adjacent to the end of the parameter adjustment period is output as the relative oscillation coefficient of the target power distribution line within any parameter adjustment period.

[0075] In this embodiment, the time series forecasting algorithm used is the exponential smoothing forecasting algorithm. In practical applications, as other implementation methods, implementers may also use other time series forecasting algorithms according to specific circumstances. This embodiment does not impose any special restrictions. The principle of the exponential smoothing forecasting algorithm is a well-known technology and will not be described in detail here.

[0076] Based on the relative oscillation coefficient, it can be understood that the relative oscillation coefficient is used to characterize the predicted state of voltage error oscillation pattern at the next moment after the end of the parameter adjustment period. It reflects the temporal evolution law based on the micro-oscillation characteristics within the parameter adjustment period and provides a forward-looking assessment of the oscillation mode that the system will face in the future short time scale. Since the relative oscillation coefficient is a single-point predicted value obtained by extrapolating the relative oscillation characteristic value through an exponential smoothing prediction algorithm, it inherits the dimensionless characteristics of the relative oscillation characteristic value. Therefore, the relative oscillation coefficient is a dimensionless parameter. The larger the relative oscillation coefficient, the more likely the line voltage error will continue to exhibit low-frequency, large-amplitude oscillation characteristics in the short term, requiring a further increase in the proportional parameter to overcome the slow response. Conversely, the smaller the relative oscillation coefficient, the more likely the line voltage error will continue to exhibit high-frequency, small-amplitude oscillation characteristics in the short term, requiring a reduction in the proportional parameter in advance to converge the dynamic process and avoid overcompensation.

[0077] Furthermore, in this embodiment, based on the relative oscillation coefficient of the target distribution line within any parameter adjustment period, and in conjunction with the impedance load coupling influence coefficient, the parameter adjustment coefficient within any parameter adjustment period is determined. Specifically:

[0078] In this embodiment, the parameter adjustment coefficient within any parameter adjustment period is positively correlated with the impedance load coupling influence coefficient and the relative oscillation coefficient, respectively.

[0079] Preferably, as one implementation method, in this embodiment, the average value of the impedance load coupling influence coefficient and the relative oscillation coefficient of the target power distribution line within any parameter adjustment period is used as the parameter adjustment coefficient within any parameter adjustment period.

[0080] Based on the parameter adjustment coefficient, it can be understood that the parameter adjustment coefficient is used to characterize the urgency and direction of adaptive adjustment of the PI controller proportional parameters after considering the comprehensive macroscopic impedance load coupling trend and the microscopic voltage error oscillation prediction. It reflects the global quantitative assessment of the overall dynamic operating conditions of the current power distribution line and the controller's response capability requirements. Since the parameter adjustment coefficient is the direct arithmetic mean of the impedance load coupling influence coefficient and the relative oscillation coefficient, and both the impedance load coupling influence coefficient and the relative oscillation coefficient are dimensionless parameters, the parameter adjustment coefficient is also dimensionless. The calculation of the parameter adjustment coefficient is positively correlated with the impedance load coupling influence coefficient and the relative oscillation coefficient. When the impedance load coupling influence coefficient and the relative oscillation coefficient are larger, the parameter adjustment coefficient is larger. This reflects that both the macroscopic voltage drop trend and the microscopic error oscillation pattern indicate that the system is in a state of extreme under-response, requiring the use of a larger proportional parameter in the next parameter adjustment period to quickly reduce the voltage error. Conversely, when the impedance load coupling influence coefficient and the relative oscillation coefficient are smaller, the parameter adjustment coefficient is smaller. This reflects that the system is in a state of over-response or light load disturbance, requiring the output of a smaller proportional parameter in the next parameter adjustment period to smooth fluctuations and ensure steady-state accuracy.

[0081] Thus, this embodiment quantifies the oscillation characteristics of micro voltage errors and predicts their future evolution trend, deeply integrates them with the coupling effect of macroscopic impedance loads, constructs parameter adjustment coefficients, realizes a forward-looking global assessment of the system's dynamic response requirements, effectively avoids control oscillations caused by blindly adjusting parameters based solely on transient oscillations, and provides a reliable basis for the safe and accurate adaptive tuning of the PI controller's proportional parameters.

[0082] Step S5: Using the parameter adjustment coefficient, adjust the proportional parameter in the PI controller within the next parameter adjustment period adjacent to any parameter adjustment period to control the voltage in the target power distribution line.

[0083] The operating state of power distribution lines evolves continuously over time. The impedance load coupling state and voltage error oscillation trend assessed in the current period directly determine the system's dynamic response capability requirements for the PI controller in the next period. Adjusting the proportional parameter based solely on a single-dimensional state assessment result can easily lead to biases and oscillations in the control strategy. Therefore, this embodiment utilizes the parameter adjustment coefficient to regulate the proportional parameter in the PI controller within the next parameter adjustment period adjacent to any parameter adjustment period, thereby controlling the voltage in the target power distribution line. Specifically:

[0084] In this embodiment, the optimized value of the proportional parameter in the PI controller during the next parameter adjustment period adjacent to parameter adjustment period b. The expression is: In the formula, This represents the parameter adjustment coefficient during the parameter adjustment period b. , represents the preset additive factor and the preset multiplicative factor, respectively; round() represents the rounding function.

[0085] Preferably, the schematic diagram of the proportional parameter adjustment process provided in this embodiment is as follows: Figure 2 As shown.

[0086] It should be noted that in this embodiment, the preset additive factor is 0.5, and the preset multiplicative factor is 12.0. This is because the proportional parameter of the PI controller is limited by the switching frequency of the power electronic devices and the system stability in practical engineering applications, and must be constrained within a feasible region. The additive factor p represents the lower limit of this feasible region (i.e., the minimum allowable proportional parameter of 0.5). Its purpose is to prevent the proportional parameter from being too small, causing the system to lose its basic voltage regulation capability. The multiplicative factor... The range of the feasible domain is represented by the interval, which determines the upper limit of the dynamic range of adaptive adjustment. Implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0087] Furthermore, during the adjacent next parameter adjustment period, the voltage error at each moment is used as the input of the PI controller. The optimized value of the proportional parameter in the PI controller during the adjacent next parameter adjustment period is used as the proportional parameter in the PI controller, and a voltage control signal is output to compensate for the voltage at each moment.

[0088] The process of using a PI controller to compensate for voltage is a well-known technique and will not be described in detail here.

[0089] Thus, this embodiment maps the parameter adjustment coefficient, which integrates macroscopic coupling trends and microscopic oscillation predictions, to the safe and feasible domain of the proportional parameter for periodic forward control. This effectively avoids the slow response and control oscillations caused by blindly adjusting parameters in a fixed or single dimension, enabling the dynamic voltage restorer to match the dynamic evolution requirements of the circuit and improving the steady-state control accuracy and response speed of voltage compensation.

[0090] Based on the same inventive concept as the above method, this application embodiment also provides a closed-loop adaptive control system for power distribution line voltage compensation, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described closed-loop adaptive control methods for power distribution line voltage compensation.

[0091] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0092] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0093] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A closed-loop adaptive control method for voltage compensation in power distribution lines, characterized in that, The method includes the following steps: Collect various electrical parameter signals of the target power distribution line, including voltage signals, current signals, and voltage error signals; Within the preset parameter adjustment period, a sliding time window is processed for each electrical parameter signal, and the impedance and average line load rate of the target power distribution line are calculated based on the current and voltage signals within each time window. During any parameter adjustment period, the impedance-load coupling influence coefficient of the target distribution line is quantified by analyzing the changing trends of the target distribution line impedance and the average line load rate. The oscillation frequency and amplitude of the voltage error signal within each time window are analyzed to determine the relative oscillation characteristic value, so as to construct the relative oscillation coefficient of the target distribution line within any parameter adjustment period. Combined with the impedance load coupling influence coefficient, the parameter adjustment coefficient within any parameter adjustment period is determined. Using the parameter adjustment coefficient, the proportional parameter in the PI controller is adjusted within the next parameter adjustment period adjacent to any parameter adjustment period in order to control the voltage in the target power distribution line.

2. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 1, characterized in that, The quantification process of the impedance load coupling influence coefficient is as follows: During any parameter adjustment period, the trend term sequence of the target distribution line impedance and the trend term sequence of the average line load rate are extracted using the time series decomposition algorithm. Fit all elements of the trend term sequence of impedance and all elements of the trend term sequence of average line load rate respectively, and normalize the slope of their respective fitted lines, which are denoted as the first trend value and the second trend value respectively. Based on the first trend value and the second trend value, the impedance load coupling influence coefficient of the target power distribution line is determined within any parameter adjustment period.

3. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 2, characterized in that, The impedance load coupling influence coefficient of the target power distribution line during the adjustment period of any parameter is the average of the first trend value and the second trend value.

4. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 1, characterized in that, The process for determining the relative oscillation characteristic value is as follows: Within any parameter adjustment period, calculate the normalized value of the zero-crossing rate of the voltage error signal in each time window, and record it as the relative oscillation frequency of the voltage error signal in each time window. The peak-to-peak value of the voltage error signal within each time window is normalized and used as the relative oscillation amplitude of the voltage error signal within each time window. Based on the relative oscillation frequency and the relative oscillation amplitude, the relative oscillation characteristic values ​​under each time window are determined.

5. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 4, characterized in that, The relative oscillation characteristic values ​​under each time window are positively correlated with the relative oscillation amplitude and negatively correlated with the relative oscillation frequency.

6. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 5, characterized in that, The process for constructing the relative oscillation coefficient of the target distribution line during the adjustment period of any parameter is as follows: The relative oscillation characteristic values ​​under all time windows within any parameter adjustment period are used as input to the time series prediction algorithm. The predicted value of the relative oscillation characteristic value at the next time adjacent to the end of the parameter adjustment period is output as the relative oscillation coefficient of the target distribution line within any parameter adjustment period.

7. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 1, characterized in that, The parameter adjustment coefficients within any parameter adjustment period are positively correlated with the impedance load coupling influence coefficient and the relative oscillation coefficient, respectively.

8. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 1, characterized in that, The adjustment of the proportional parameter in the PI controller within the next parameter adjustment period adjacent to any parameter adjustment period includes: The optimized value of the proportional parameter in the PI controller during the next adjacent parameter adjustment period b. The expression is: In the formula, This represents the parameter adjustment coefficient during the parameter adjustment period b. , represents the preset additive factor and the preset multiplicative factor, respectively; round() represents the rounding function.

9. The closed-loop adaptive control method for voltage compensation of power distribution lines as described in claim 8, characterized in that, The control of voltage in the target power distribution line includes: During the adjacent next parameter adjustment period, the voltage error at each moment is used as the input of the PI controller. The optimized value of the proportional parameter in the PI controller during the adjacent next parameter adjustment period is used as the proportional parameter in the PI controller, and a voltage control signal is output to compensate for the voltage at each moment.

10. A closed-loop adaptive control system for voltage compensation of power distribution lines, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the closed-loop adaptive control method for voltage compensation of power distribution lines as described in any one of claims 1-9.

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