A method and system for optimizing reactive power control in regional power grid

Abstract

The present invention relates to the technical field of power grid optimization, and in particular to a method and system for optimizing reactive power of a regional power grid, including establishing a dynamic response matrix according to key characteristic parameters of reactive compensation equipment in a regional power grid; dynamically tracking the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive demand change trend; determining the target output adjustment value of each reactive compensation equipment according to the reactive demand change trend; generating an output adjustment control instruction according to the target output adjustment value; adjusting the reactive output of each reactive compensation equipment according to the output adjustment control instruction, and dynamically adjusting the output limit of the reactive compensation equipment according to the equipment operation status and reactive power data of the reactive compensation equipment during the reactive output adjustment process of the reactive compensation equipment. The present invention realizes precise control and optimization adjustment of the output of the reactive compensation equipment by dynamically adjusting the output limit of the reactive compensation equipment, thereby improving the reactive compensation efficiency of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid optimization, and in particular to a method and system for optimizing reactive power control of a regional power grid. Background Art

[0002] With the development and complexity of power systems, the problem of reactive power optimization in regional power grids has become increasingly prominent. Reactive power optimization is a key link to ensure stable operation of the power grid and improve power quality. Currently, there are many types of reactive power compensation equipment in regional power grids, such as shunt capacitors, static VAR generators (SVGs), etc. The response speeds and adjustment capabilities of these devices vary, making it difficult to achieve efficient reactive power optimization in actual operation.

[0003] Different types of reactive power compensation equipment have significant differences in response speed and regulation capabilities. For example, parallel capacitors have the characteristics of fast response, but their output regulation usually relies on group switching, with a relatively slow response speed and inability to achieve continuous regulation. In contrast, SVGs have higher regulation flexibility and dynamic response capabilities, but their construction and operation and maintenance costs are high. Existing technologies often independently control the output limits of these devices and lack a unified coordination mechanism. This control method not only makes it difficult to give full play to the advantages of various types of equipment, but also leads to unreasonable resource allocation, affecting the overall efficiency of reactive power optimization. In addition, with the large-scale access of renewable energy, the reactive power demand of regional power grids has become more complex and changeable. The output of renewable energy such as wind power and solar energy is intermittent and uncertain, making it difficult to predict and stably control the reactive power demand of the power grid. The traditional reactive power compensation equipment output limit control method has been difficult to adapt to this complex and changeable reactive power demand, resulting in severe challenges for the power grid in terms of reactive power balance and voltage stability.

[0004] Therefore, the reactive power optimization control in the current regional power grid faces many challenges. How to dynamically adjust the output limits of different types of reactive power compensation equipment has become a technical problem that needs to be solved urgently in the field of reactive power optimization in the current regional power grid. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and system for optimizing reactive power control of a regional power grid.

[0006] In a first aspect, the present invention provides a method for optimizing reactive power control in a regional power grid, the method comprising the following steps:

[0007] Real-time collection of key characteristic parameters of reactive power compensation equipment in the regional power grid, and establishment of a dynamic response matrix based on the key characteristic parameters;

[0008] Dynamically track the reactive power flow of the power grid based on the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within the future preset time period;

[0009] Determining a target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters;

[0010] Generate output regulation control instructions according to the target output regulation value of each reactive power compensation device;

[0011] The reactive output of each reactive compensation device is adjusted in real time according to the output adjustment control instruction, and during the reactive output adjustment process of the reactive compensation device, the output limit of the reactive compensation device is dynamically adjusted according to the device operation status and reactive power data of the reactive compensation device.

[0012] In a further embodiment, the step of real-time acquisition of key characteristic parameters of reactive power compensation equipment in the regional power grid includes:

[0013] Collecting compensation voltage and current signals of reactive power compensation equipment from the regional power grid in real time, and calculating the actual operating capacity value of the reactive power compensation equipment based on the compensation voltage and current signals;

[0014] Constructing a voltage response curve of a reactive power compensation device according to the actual operating capacity value, and performing piecewise linear fitting on the voltage response curve using a sliding time window to obtain a fitting curve;

[0015] According to the slope change rate of the fitting curve, the dynamic response time point is identified;

[0016] Acquire an actual value of a voltage variation of the reactive power compensation device, and analyze the actual value of the voltage variation by using a recursive least square method with a forgetting factor to obtain a voltage variation prediction value;

[0017] Calculating the adjustment accuracy value of the reactive power compensation device according to the difference between the actual value of the voltage change and the predicted value of the voltage change;

[0018] The key characteristic parameters of the reactive compensation equipment are generated according to the actual operating capacity value, dynamic response time point, dynamic response dead zone range value and adjustment accuracy value of the reactive compensation equipment; wherein the key characteristic parameters include available capacity, dynamic response time, adjustment accuracy value and dynamic response dead zone.

[0019] In a further embodiment, the step of establishing a dynamic response matrix according to the key characteristic parameters comprises:

[0020] Arranging the key characteristic parameters in a predetermined order to construct a characteristic parameter vector;

[0021] Calculate the sliding variance value of the characteristic parameter vector in different sliding windows and construct the fluctuation characteristic matrix;

[0022] The fluctuation characteristic matrix is ​​processed by using an exponentially weighted moving average method to generate a prediction sequence;

[0023] Calculating a root mean square error of the prediction sequence, and determining a steady-state interval according to the root mean square error;

[0024] Select the characteristic submatrix corresponding to the steady-state interval from the fluctuation characteristic matrix;

[0025] Performing singular value decomposition on the characteristic submatrix, and selecting eigenvectors corresponding to the first several largest singular values ​​to construct a stable subspace;

[0026] In the stable subspace, the stability index value corresponding to each singular value is calculated. If the stability index value is less than a preset stability threshold, the current characteristic submatrix is ​​determined as the dynamic response matrix of the reactive compensation device.

[0027] In a further embodiment, the step of establishing a dynamic response matrix according to the key characteristic parameters further includes:

[0028] Generate an initial response prediction curve of the reactive compensation device according to the dynamic response matrix, and iteratively optimize the initial response prediction curve using a gradient descent algorithm to minimize the difference between the initial response prediction curve and the actual response, so as to obtain an optimized prediction curve;

[0029] Performing parameter correction on the fluctuation characteristic matrix according to the optimized prediction curve to obtain a corrected fluctuation characteristic matrix;

[0030] The dynamic response matrix of the reactive power compensation device is updated according to the modified fluctuation characteristic matrix.

[0031] In a further implementation scheme, the step of dynamically tracking the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within a preset time period in the future includes:

[0032] Analyze the dynamic response characteristics of the reactive compensation equipment according to the dynamic response matrix, and construct a capacity attenuation characteristic curve of the reactive compensation equipment that changes with time;

[0033] Calculate the difference between the reactive capacity and the rated capacity of each reactive compensation device in the current state according to the capacity attenuation characteristic curve to obtain a reactive shortage data set;

[0034] Collecting voltage amplitude data of the power grid branch, and smoothing the voltage amplitude data using the Kalman filter method to obtain smoothed voltage amplitude data;

[0035] Integrating the smoothed voltage amplitude data and the reactive power shortage data set with the topological structure information of the power grid branch to obtain an operation state vector of the power grid branch;

[0036] Extracting reactive power flow components from the operation state vector of the power grid branch, dynamically predicting the reactive power flow components using an adaptive exponential smoothing method, and obtaining reactive power flow component prediction results;

[0037] According to the reactive power flow component prediction result and the impedance parameter of the power grid branch, reactive power flow transmission data on the power grid branch is obtained through power flow calculation;

[0038] The reactive power flow transmission data is fitted by using cubic polynomial fitting to predict the reactive power demand change trend of the regional power grid within a preset time period in the future.

[0039] In a further embodiment, the step of determining the target output adjustment value of each reactive compensation device according to the reactive demand change trend and the key characteristic parameter comprises:

[0040] According to the trend of reactive power demand, the reactive power demand of the power grid at different time points is extracted at preset fixed time intervals;

[0041] Quantifying the reactive power demand according to the regulation accuracy value of the reactive power compensation device to obtain the expected regulation step length of the reactive power compensation device at different time points;

[0042] Generate a response curve of the reactive compensation device under reactive demand changes according to the expected adjustment step length of the reactive compensation device at different time points;

[0043] Each time point on the response curve is traversed, and a target output adjustment value is obtained according to the response curve and the actual adjustment capability of the reactive power compensation device at the current time point.

[0044] In a further embodiment, the step of generating a response curve of the reactive power compensation device under reactive power demand changes according to the expected adjustment step of the reactive power compensation device at different time points comprises:

[0045] According to the rated power of the reactive power compensation equipment, the switching loss and conduction loss corresponding to the unit compensation amount are calculated;

[0046] Performing a weighted summation of the switching loss and the conduction loss to obtain a compensation loss coefficient;

[0047] A response curve of the reactive power compensation device under reactive power demand changes is generated according to the compensation loss coefficient and the expected adjustment step size.

[0048] In a further embodiment, the step of adjusting the reactive output of each reactive compensation device in real time according to the output adjustment control instruction includes:

[0049] In response to the received output regulation control instruction, a time difference between the execution time of the output regulation control instruction and the current system time is calculated using a network time protocol;

[0050] According to the time difference, the command execution delay of the output regulation control command is predicted by the Kalman filter algorithm;

[0051] According to the instruction, the real-time operating parameters of each reactive compensation device are collected in a delayed manner, and the actual reactive output value of each reactive compensation device at the current moment is calculated based on the real-time operating parameters;

[0052] According to the deviation between the actual reactive power output value of each reactive power compensation device and the preset target output value, the reactive power output adjustment control value is calculated by using a proportional integral controller;

[0053] The reactive output regulation control value is smoothed by using a cubic spline curve interpolation method to obtain a smooth regulation curve;

[0054] Extract reactive power output data at each time point from the smooth adjustment curve, and generate a feedback information packet according to the reactive power output data and the instruction execution delay;

[0055] The reactive output of the reactive compensation equipment is adjusted in real time according to the feedback information package until the reactive output of each reactive compensation equipment stably reaches the target output value.

[0056] In a further embodiment, during the reactive output regulation process of the reactive compensation device, the step of dynamically adjusting the output limit of the reactive compensation device according to the device operating status and reactive power data of the reactive compensation device comprises:

[0057] Acquire the equipment operation status and reactive power data of reactive compensation equipment in real time at a preset sampling period;

[0058] According to the reactive power data and the operating status of the equipment, a recursive least squares algorithm is used to obtain the reactive power shortage value and reactive power shortage change rate of the current power grid;

[0059] Determine the duration of reactive power shortage according to the time point when the reactive power shortage value occurs;

[0060] According to the reactive power shortage value, the reactive power shortage change rate and the duration of the reactive power shortage, a reactive power shortage prediction value is obtained by using an exponential smoothing prediction method;

[0061] Calculate the required compensation capacity according to the reactive power shortage prediction value, and decompose the compensation capacity into grades to generate a graded compensation instruction sequence; the compensation capacity is the reactive power required by the reactive power compensation device;

[0062] According to the hierarchical compensation instruction sequence and the operating status of the equipment, the output limit of the reactive power compensation equipment is adjusted to dynamically compensate for the reactive power shortage of the power grid.

[0063] In a second aspect, the present invention provides a regional power grid reactive power optimization control system, the system comprising:

[0064] A data acquisition module is used to collect key characteristic parameters of reactive power compensation equipment in a regional power grid in real time, and to establish a dynamic response matrix based on the key characteristic parameters;

[0065] The power flow tracking module is used to dynamically track the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line, and obtain the reactive power demand change trend within the future preset time period;

[0066] An output analysis module, used to determine the target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters;

[0067] An instruction generation module is used to generate an output regulation control instruction according to the target output regulation value of each reactive power compensation device;

[0068] The output regulation module is used to adjust the reactive output of each reactive compensation device in real time according to the output regulation control instruction, and during the reactive output regulation process of the reactive compensation device, dynamically adjust the output limit of the reactive compensation device according to the device operating status and reactive power data of the reactive compensation device.

[0069] The present invention provides a method and system for optimizing reactive power control of a regional power grid. The method collects key characteristic parameters of reactive compensation equipment in a regional power grid in real time, and establishes a dynamic response matrix according to the key characteristic parameters; dynamically tracks the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line, and obtains the reactive demand change trend in the future preset time period; determines the target output adjustment value of each reactive compensation equipment according to the reactive demand change trend and the key characteristic parameters; generates an output adjustment control instruction according to the target output adjustment value of each reactive compensation equipment; adjusts the reactive output of each reactive compensation equipment in real time according to the output adjustment control instruction, and dynamically adjusts the output limit of the reactive compensation equipment according to the equipment operation status and reactive power data of the reactive compensation equipment during the reactive output adjustment process of the reactive compensation equipment. Compared with the prior art, the method dynamically adjusts the output limit of various reactive compensation equipment by constructing technologies such as a dynamic response matrix, realizes the precise control and optimization adjustment of the output of the reactive compensation equipment, improves the reactive compensation efficiency, enhances the stability and voltage support capacity of the power grid, and reduces equipment loss and operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a schematic flow chart of a method for optimizing reactive power control of a regional power grid provided by an embodiment of the present invention;

[0071] Figure 2 It is a block diagram of a regional power grid reactive power optimization control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The following specifically illustrates the implementation mode of the present invention in conjunction with the accompanying drawings. The embodiments are provided for illustrative purposes only and cannot be understood as limiting the present invention. The accompanying drawings are provided for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0073] refer to Figure 1 , the embodiment of the present invention provides a method for optimizing reactive power control of a regional power grid, such as Figure 1 As shown, the method comprises the following steps:

[0074] S1. Collect key characteristic parameters of reactive power compensation equipment in the regional power grid in real time, and establish a dynamic response matrix based on the key characteristic parameters.

[0075] In this embodiment, the step of real-time acquisition of key characteristic parameters of reactive power compensation equipment in the regional power grid includes:

[0076] Collecting compensation voltage and current signals of reactive power compensation equipment from the regional power grid in real time, and calculating the actual operating capacity value of the reactive power compensation equipment based on the compensation voltage and current signals;

[0077] Constructing a voltage response curve of a reactive power compensation device according to the actual operating capacity value, and performing piecewise linear fitting on the voltage response curve using a sliding time window to obtain a fitting curve;

[0078] According to the slope change rate of the fitting curve, the dynamic response time point is identified;

[0079] Acquire an actual value of a voltage variation of the reactive power compensation device, and analyze the actual value of the voltage variation by using a recursive least square method with a forgetting factor to obtain a voltage variation prediction value;

[0080] Calculating the adjustment accuracy value of the reactive power compensation device according to the difference between the actual value of the voltage change and the predicted value of the voltage change;

[0081] The key characteristic parameters of the reactive compensation equipment are generated according to the actual operating capacity value, dynamic response time point, dynamic response dead zone range value and adjustment accuracy value of the reactive compensation equipment; wherein the key characteristic parameters include available capacity, dynamic response time, adjustment accuracy value and dynamic response dead zone.

[0082] Specifically, this embodiment installs voltage and current sensors on the reactive compensation device, and connects the voltage and current sensors to the input and output ends of the reactive compensation device, respectively, to ensure the accuracy and reliability of signal acquisition. This embodiment collects the compensation voltage and current signals in the power grid in real time through the voltage and current sensors. The compensation voltage and current signals include compensation voltage signals and compensation current signals. The compensation voltage and current signals output by the sensor are input to an analog-to-digital converter (ADC) for digital processing after passing through a signal conditioning circuit to obtain a digital compensation voltage and current signal. According to the digital compensation voltage and current signals, the actual operating capacity value (reactive power) of the reactive compensation device is calculated using a power calculation formula. The power calculation formula is:

[0083]

[0084] In the formula, P is the actual operating capacity value of the reactive power compensation equipment; U is the compensation voltage signal; I is the compensation current signal; is the power factor angle.

[0085] Then, this embodiment uses the voltage value as the independent variable and the actual operating capacity value of the reactive compensation device as the dependent variable to construct the voltage response curve of the reactive compensation device under different voltage conditions, adopts the sliding time window algorithm to slide and segment the voltage response curve, and adopts the least squares method and other algorithms to linearly fit the data in each time window to obtain the fitting curve, and determines the slope change rate by calculating the slope difference of adjacent time periods, wherein the size of the sliding time window should be selected according to the dynamic response characteristics of the reactive compensation device, and this embodiment identifies the points where the slope changes significantly as the dynamic response time points according to the slope change rate of the fitting curve, these points represent the key time points when the reactive compensation device responds to the grid voltage change, and the threshold value of the slope change rate should be set according to the dynamic response characteristics of the reactive compensation device, then, this embodiment calculates the actual value of the voltage change of the reactive compensation device according to the collected voltage signal, and adopts the recursive least squares method with a forgetting factor to calculate the voltage change. The actual value of the amount is modeled and predicted to obtain a voltage change prediction value, wherein the forgetting factor can be selected between 0.95 and 1 to balance the influence of historical data. In this embodiment, the adjustment accuracy value of the reactive compensation device is evaluated by comparing the error between the actual value of the voltage change and the predicted value. The adjustment accuracy value can be determined by relative error or absolute error. The smaller the error, the higher the adjustment accuracy. For example, the adjustment accuracy can be expressed as a root mean square error (RMSE) of the difference or other indicators. In this embodiment, the key characteristic parameters of the reactive compensation device are generated according to the actual operating capacity value, dynamic response time point, dynamic response dead zone range value and adjustment accuracy value of the reactive compensation device. The key characteristic parameters include rated capacity (which can be obtained or preset through the device nameplate), available capacity (calculated according to the ratio of the actual operating capacity value to the rated capacity), dynamic response time (the time difference between the dynamic response time point and the triggering moment), adjustment accuracy and dynamic response dead zone, so as to provide data support for the optimized operation of the power grid.

[0086] After obtaining the key characteristic parameters of the reactive power compensation device, this embodiment accurately predicts and controls the flow of reactive power in the power grid based on the key characteristic parameters of the reactive power compensation device, thereby constructing a dynamic response matrix. In this embodiment, the step of establishing the dynamic response matrix according to the key characteristic parameters includes:

[0087] Arranging the key characteristic parameters in a predetermined order to construct a characteristic parameter vector;

[0088] Calculate the sliding variance value of the characteristic parameter vector in different sliding windows and construct the fluctuation characteristic matrix;

[0089] The fluctuation characteristic matrix is ​​processed by using an exponentially weighted moving average method to generate a prediction sequence;

[0090] Calculating a root mean square error of the prediction sequence, and determining a steady-state interval according to the root mean square error;

[0091] Select the characteristic submatrix corresponding to the steady-state interval from the fluctuation characteristic matrix;

[0092] Performing singular value decomposition on the characteristic submatrix, and selecting eigenvectors corresponding to the first several largest singular values ​​to construct a stable subspace;

[0093] In the stable subspace, the stability index value corresponding to each singular value is calculated. If the stability index value is less than a preset stability threshold, the current characteristic submatrix is ​​determined as the dynamic response matrix of the reactive compensation device.

[0094] Specifically, this embodiment arranges the key characteristic parameters according to importance, for example: [available capacity, dynamic response time, adjustment accuracy value, dynamic response dead zone], to form a characteristic parameter vector, and determines the size of the sliding window according to the number of data points included in each variance calculation, and for each parameter in the characteristic parameter vector, calculates its variance value in each sliding window to form multiple variance value sequences, and combines the variance value sequences of each parameter in different sliding windows into a fluctuation feature matrix, wherein the rows of the matrix represent different characteristic parameters, and the columns represent the variance value sequences of each sliding window; then, the weight attenuation coefficient is set according to the exponentially weighted moving average method, and according to the actual observation values ​​at different time points, the exponentially weighted moving average method is used to calculate each column in the fluctuation feature matrix to obtain the corresponding prediction sequence, and the exponentially weighted moving average method can give a higher weight to recent data, thereby more sensitively reflecting the recent change trend of the data, and for each prediction sequence, calculate its variance with the predicted sequence. The root mean square error (RMSE) of the actual data is calculated, and an error threshold is set. The interval with a root mean square error less than the error threshold is regarded as a steady-state interval. According to the determined steady-state interval, the characteristic submatrix corresponding to the steady-state interval is screened out from the fluctuation characteristic matrix, and the singular value decomposition (SVD) is performed on the characteristic submatrix. According to the size of the singular value, the eigenvectors corresponding to the first several largest singular values ​​are selected. These eigenvectors constitute the basis of the stable subspace. In the stable subspace, the stability index value corresponding to each singular value is calculated by analyzing the rate of change and correlation of the eigenvectors. At the same time, a stability threshold is set, and the characteristic submatrix with a stability index value less than the stability threshold is regarded as a dynamic response matrix that meets the requirements. If the current characteristic submatrix meets the stability condition, it is used as the dynamic response matrix of the reactive compensation device, thereby realizing the construction of the dynamic response matrix of the reactive compensation device in the regional power grid, and providing an accurate mathematical model basis for the subsequent reactive optimization control.

[0095] In this embodiment, after the step of establishing a dynamic response matrix according to the key characteristic parameters, the step further includes:

[0096] Generate an initial response prediction curve of the reactive compensation device according to the dynamic response matrix, and iteratively optimize the initial response prediction curve using a gradient descent algorithm to minimize the difference between the initial response prediction curve and the actual response, so as to obtain an optimized prediction curve;

[0097] Performing parameter correction on the fluctuation characteristic matrix according to the optimized prediction curve to obtain a corrected fluctuation characteristic matrix;

[0098] The dynamic response matrix of the reactive power compensation device is updated according to the modified fluctuation characteristic matrix.

[0099] Specifically, this embodiment uses the operation status data of the power grid (such as load changes, voltage fluctuations, etc.) as input, combines the established dynamic response matrix, maps the input data to the dynamic response matrix, obtains the predicted output response, and plots the generated predicted output response in the form of a curve to form an initial response prediction curve of the reactive compensation device. In order to quantify the difference between the initial response prediction curve and the actual response, this embodiment defines a mean square error loss function or an absolute error loss function. The goal of the loss function is to minimize the difference between the predicted value and the actual value, and the gradient descent algorithm is used to optimize the loss function. The specific implementation process is:

[0100] This embodiment calculates the gradient of the loss function with respect to each parameter in the dynamic response matrix; then, updates the parameter value of the dynamic response matrix according to the gradient information to gradually reduce the value of the loss function. This process requires multiple iterations until the value of the loss function reaches a preset convergence condition (such as the loss value is less than a certain threshold, or the gradient value is close to zero). After multiple iterations, when the loss function converges, an optimized dynamic response matrix and a corresponding optimized prediction curve are obtained. The optimized prediction curve is closer to the actual response, thereby improving the accuracy of the prediction.

[0101] This embodiment observes the shape and trend of the optimized prediction curve and analyzes the relationship between it and the fluctuation characteristic matrix. The optimized prediction curve reflects the response of the reactive compensation equipment at different time points, and the fluctuation characteristic matrix describes the fluctuation characteristics of these responses. The parameters in the fluctuation characteristic matrix are corrected based on the analysis results of the optimized prediction curve. Specifically, this can be achieved by adjusting the element values ​​in the fluctuation characteristic matrix so that the fluctuation characteristic matrix can better reflect the actual response characteristics of the reactive compensation equipment. After the parameter correction, the corrected fluctuation characteristic matrix is ​​obtained. The corrected fluctuation characteristic matrix more accurately describes the response fluctuation characteristics of the reactive compensation equipment. Finally, the corrected fluctuation characteristic matrix is ​​used in combination with the operation of the power grid. The updated dynamic response matrix can be applied to the actual operation of the power grid for verification and testing. By comparing the difference between the predicted response and the actual response, the accuracy and reliability of the updated dynamic response matrix can be evaluated. If the verification result shows that there is still a large difference between the predicted response and the actual response, the above steps are repeated to further iterate and optimize the dynamic response matrix. Through continuous iteration and optimization, the accuracy and adaptability of the dynamic response matrix can be gradually improved, so that the dynamic response matrix of the reactive compensation equipment can be accurately constructed and optimized, thereby improving the efficiency and accuracy of reactive compensation of the power grid.

[0102] S2. Dynamically track the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within the future preset time period.

[0103] In this embodiment, the step of dynamically tracking the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within the future preset time period includes:

[0104] Analyze the dynamic response characteristics of the reactive compensation equipment according to the dynamic response matrix, and construct a capacity attenuation characteristic curve of the reactive compensation equipment that changes with time;

[0105] Calculate the difference between the reactive capacity and the rated capacity of each reactive compensation device in the current state according to the capacity attenuation characteristic curve to obtain a reactive shortage data set;

[0106] Collecting voltage amplitude data of the power grid branch, and smoothing the voltage amplitude data using the Kalman filter method to obtain smoothed voltage amplitude data;

[0107] Integrating the smoothed voltage amplitude data and the reactive power shortage data set with the topological structure information of the power grid branch to obtain an operation state vector of the power grid branch;

[0108] Extracting reactive power flow components from the operation state vector of the power grid branch, dynamically predicting the reactive power flow components using an adaptive exponential smoothing method, and obtaining reactive power flow component prediction results;

[0109] According to the reactive power flow component prediction result and the impedance parameter of the power grid branch, reactive power flow transmission data on the power grid branch is obtained through power flow calculation;

[0110] The reactive power flow transmission data is fitted by using cubic polynomial fitting to predict the reactive power demand change trend of the regional power grid within a preset time period in the future.

[0111] Specifically, this embodiment collects historical operating data of reactive compensation equipment, the historical operating data includes factors affecting equipment performance such as reactive compensation amount, equipment age, and operating temperature, and uses a dynamic response matrix to analyze the response characteristics of the reactive compensation equipment under different working conditions, especially the capacity attenuation that changes with time. Based on the collected data and the analysis results of the dynamic response matrix, a capacity attenuation characteristic curve of the reactive compensation equipment that changes with time is constructed using data fitting technology (such as nonlinear regression). The curve reflects the law of equipment capacity attenuation over time, and then the actual operating data of the reactive compensation equipment at the current time point is obtained. The historical operating data includes the actual reactive compensation amount. According to the capacity attenuation characteristic curve, the difference between the reactive capacity and the rated capacity of each reactive compensation equipment in the current state is calculated, that is, the reactive shortage. The reactive shortage data of all reactive compensation equipment are organized into a reactive shortage data set for subsequent analysis.

[0112] Next, this embodiment uses sensors to collect voltage amplitude data of power grid branches in real time, and smoothes the collected voltage amplitude data through the Kalman filtering method to reduce the influence of noise and outliers, so as to obtain smoothed voltage amplitude data, and at the same time obtains the topological structure information of the power grid branch. The topological structure information of the power grid branch includes the connection relationship of the branch, transformer parameters, etc. The smoothed voltage amplitude data, reactive power shortage data set and topological structure information of the power grid branch are integrated into a comprehensive operating state vector. This operating state vector comprehensively reflects the current operating state of the power grid branch. The reactive power flow component, that is, the reactive power flow on the power grid branch, is extracted from the operating state vector. The extracted reactive power flow component is dynamically predicted by the adaptive exponential smoothing method to obtain the reactive power flow component prediction result in the future period of time. The adaptive exponential smoothing method can automatically adjust the smoothing coefficient according to the change of data to improve the accuracy of the prediction.

[0113] This embodiment calculates reactive power flow transmission data on the power grid branch according to the reactive power flow component prediction result and the impedance parameters of the power grid branch by using a power flow calculation method (such as the Newton-Raphson method or the DC power flow method). These data reflect the reactive power flow on the power grid branch in the future. The calculated reactive power flow transmission data is used as input, and a cubic polynomial fitting method is used to fit these data. The cubic polynomial fitting can better reflect the nonlinear change trend of the data. According to the cubic polynomial model obtained by fitting, the reactive power demand change trend in the future preset time period is predicted. This trend reflects the reactive power demand of the power grid in the future, thereby realizing dynamic tracking and prediction of the reactive power flow of the power grid, and providing strong support for reactive power compensation and voltage control of the power grid.

[0114] S3. Determine the target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters.

[0115] In this embodiment, the step of determining the target output adjustment value of each reactive compensation device according to the reactive demand change trend and the key characteristic parameter includes:

[0116] According to the trend of reactive power demand, the reactive power demand of the power grid at different time points is extracted at preset fixed time intervals;

[0117] Quantifying the reactive power demand according to the regulation accuracy value of the reactive power compensation device to obtain the expected regulation step length of the reactive power compensation device at different time points;

[0118] Generate a response curve of the reactive compensation device under reactive demand changes according to the expected adjustment step length of the reactive compensation device at different time points;

[0119] Each time point on the response curve is traversed, and a target output adjustment value is obtained according to the response curve and the actual adjustment capability of the reactive power compensation device at the current time point.

[0120] In the power system, reactive power compensation is an important means to maintain grid voltage stability and reduce power loss. In order to achieve accurate reactive power compensation, this embodiment determines the target output adjustment value of each reactive power compensation device according to the reactive power demand change trend of the grid and the characteristic parameters of the reactive power compensation device. Specifically, this embodiment sets a fixed time interval (such as every minute, every hour, etc.) according to the actual situation and adjustment requirements of the grid, extracts reactive power demand at different time points from the reactive power demand data according to the set fixed time interval, and then quantifies the extracted reactive power demand according to the adjustment accuracy value of the reactive power compensation device to obtain the expected adjustment step of the device at different time points. For example, if the adjustment accuracy of the device is 10kVar, and the reactive power demand at a certain hour is 123.7kVar, then after quantification, the expected adjustment step at this time point is 120kVar. The expected adjustment step at each time point is organized in chronological order to obtain the response curve of the reactive power compensation device under the change of reactive power demand. For example, assuming that this embodiment extracts the reactive power demand for 24 hours, and obtains each reactive power demand after quantification. The expected adjustment step at the time point can be used to draw a response curve from 0 to 24 o'clock, where the x-axis represents time and the y-axis represents the expected adjustment step. Starting from the starting point of the response curve, each time point is traversed one by one. At each time point, the current output, maximum output, adjustment speed and other parameters of the device are considered to determine whether the actual adjustment capacity of the reactive power compensation device meets the requirements of the expected adjustment step. If the actual adjustment capacity of the device meets the requirements, the expected adjustment step is used as the target output adjustment value; if it does not meet the requirements, it is necessary to adjust according to the actual adjustment capacity of the device to obtain a feasible target output adjustment value. For example, assuming that at a certain time point, the expected adjustment step of the device is 150kVar, but the current output of the device has reached its maximum output of 120kVar, and the adjustment speed is slow and cannot reach 150kVar in a short time, then, in this embodiment, the target output adjustment value can be set to the maximum output of the device, 120kVar, and the output of the device can be gradually adjusted at subsequent time points to meet the changes in reactive power demand as much as possible, thereby achieving accurate reactive power compensation.

[0121] In this embodiment, the step of generating a response curve of the reactive compensation device under reactive demand changes according to the expected adjustment step length of the reactive compensation device at different time points includes:

[0122] According to the rated power of the reactive power compensation equipment, the switching loss and conduction loss corresponding to the unit compensation amount are calculated;

[0123] Performing a weighted summation of the switching loss and the conduction loss to obtain a compensation loss coefficient;

[0124] A response curve of the reactive power compensation device under reactive power demand changes is generated according to the compensation loss coefficient and the expected adjustment step size.

[0125] In the power system, in order to optimize the operating efficiency of the reactive compensation equipment and reduce the loss, this embodiment needs to consider the rated power, switching loss, conduction loss and expected adjustment step of the equipment to generate the response curve of the reactive compensation equipment under the change of reactive demand. Specifically, this embodiment obtains the rated power, switching frequency, switch resistance, on-resistance and other key parameters of the reactive compensation equipment, and calculates the switching loss corresponding to the unit compensation amount according to the rated power and switching parameters of the equipment. According to the rated power and conduction parameters of the equipment, the conduction loss corresponding to the unit compensation amount is calculated. For example, assuming that the rated power of a reactive compensation equipment is 100kVar, the switching frequency is 50Hz, the switch resistance is 0.01Ω, and the on-resistance is 0.001Ω, this embodiment can use the following formula to calculate the switching loss and conduction loss corresponding to the unit compensation amount (assuming it is 1kVar), and the calculation formula of the switching loss is:

[0126]

[0127] In the formula, is the switching loss; is the switching frequency; is the switch resistance; is the current flowing through the switch; D is the duty cycle of the switch (i.e. the proportion of time the switch is turned on in one cycle).

[0128] The calculation formula for conduction loss is:

[0129]

[0130] In the formula, is the conduction loss; is the current flowing through the conducting part; is the on-resistance.

[0131] In this embodiment, the weights of switching loss and conduction loss are determined according to the characteristics of the device, the switching loss and conduction loss are multiplied by their respective weights, and then the sum is obtained to obtain the compensation loss coefficient. According to the range of changes in the reactive power demand of the power grid, the compensation amount range of the reactive power compensation device is determined. For each expected adjustment step (i.e., each compensation amount), the compensation loss coefficient is multiplied by the compensation amount to obtain the total loss under the compensation amount. Each compensation amount and its corresponding total loss are plotted on a coordinate graph, with the horizontal axis representing the compensation amount (i.e., the expected adjustment step) and the vertical axis representing the total loss, to obtain a response curve of the reactive power compensation device under changes in reactive power demand. For example, assuming that the adjustment step range of the reactive power compensation device expected in this embodiment is 0-100 kVar and the step is 1 kVar, for each adjustment step, this embodiment calculates the corresponding total loss (using the compensation loss coefficient obtained previously multiplied by the step), and plots the result on the coordinate graph, thereby obtaining a response curve reflecting the change in total loss of the reactive power compensation device under different compensation amounts.

[0132] S4. Generate an output regulation control instruction according to the target output regulation value of each reactive power compensation device.

[0133] S5. Adjust the reactive output of each reactive compensation device in real time according to the output adjustment control instruction, and dynamically adjust the output limit of the reactive compensation device according to the device operating status and reactive power data of the reactive compensation device during the reactive output adjustment process of the reactive compensation device.

[0134] In this embodiment, the step of adjusting the reactive output of each reactive compensation device in real time according to the output adjustment control instruction includes:

[0135] In response to the received output regulation control instruction, a time difference between the execution time of the output regulation control instruction and the current system time is calculated using a network time protocol;

[0136] According to the time difference, the command execution delay of the output regulation control command is predicted by the Kalman filter algorithm;

[0137] According to the instruction, the real-time operating parameters of each reactive compensation device are collected in a delayed manner, and the actual reactive output value of each reactive compensation device at the current moment is calculated based on the real-time operating parameters;

[0138] According to the deviation between the actual reactive power output value of each reactive power compensation device and the preset target output value, the reactive power output adjustment control value is calculated by using a proportional integral controller;

[0139] The reactive output regulation control value is smoothed by using a cubic spline curve interpolation method to obtain a smooth regulation curve;

[0140] Extract reactive power output data at each time point from the smooth adjustment curve, and generate a feedback information packet according to the reactive power output data and the instruction execution delay;

[0141] The reactive output of the reactive compensation equipment is adjusted in real time according to the feedback information package until the reactive output of each reactive compensation equipment stably reaches the target output value.

[0142] Specifically, the output regulation control instruction may include a control mode, an output limit value, and an execution cycle. This embodiment uses the Network Time Protocol (NTP) to synchronize and calibrate the time of all relevant devices. When receiving the output regulation control instruction, the system first records the current system time Tcurrent, then parses the execution time Texecute in the output regulation control instruction, and calculates the time difference ΔT between the current system time Tcurrent and the current system time Tcurrent. =Texecute–Tcurrent, this embodiment sets a historical delay database to record the execution delay of past instructions, combines the current time difference and historical data, and uses the Kalman filter algorithm to predict the future instruction execution delay. Within the predicted instruction execution delay, the system collects the real-time operating parameters such as voltage and current of each reactive compensation device through sensors or communication interfaces in real time, and calculates the actual reactive output value of each reactive compensation device at the current moment based on these real-time operating parameters using the reactive power calculation formula, and then calculates the deviation between the actual reactive output value of each reactive compensation device and the target output value, and inputs the deviation into the proportional integral (PI) controller, and calculates the reactive output regulation control according to the preset proportional (P) and integral (I) coefficients. The reactive output regulation control value is smoothed by using the cubic spline curve interpolation method to eliminate mutations and jitters in the regulation process, and a smooth regulation curve is obtained. On the smooth regulation curve, the reactive output data of each time point is extracted according to a preset time interval, and the extracted reactive output data, instruction execution delay and other relevant information are packaged into a feedback information package. The system generates an adjustment instruction according to the reactive output data and instruction execution delay in the feedback information package and sends it to each reactive compensation device. The system monitors the reactive output of each reactive compensation device in real time, and adjusts the adjustment instruction as needed until the reactive output of each device stably reaches the target output value, thereby being able to accurately and smoothly adjust the reactive output of each reactive compensation device to achieve reactive power balance and stable operation of the power system.

[0143] In this embodiment, during the reactive output regulation process of the reactive compensation device, the step of dynamically adjusting the output limit of the reactive compensation device according to the device operating status and reactive power data of the reactive compensation device includes:

[0144] Acquire the equipment operation status and reactive power data of reactive compensation equipment in real time at a preset sampling period;

[0145] According to the reactive power data and the operating status of the equipment, a recursive least squares algorithm is used to obtain the reactive power shortage value and reactive power shortage change rate of the current power grid;

[0146] Determine the duration of reactive power shortage according to the time point when the reactive power shortage value occurs;

[0147] According to the reactive power shortage value, the reactive power shortage change rate and the duration of the reactive power shortage, a reactive power shortage prediction value is obtained by using an exponential smoothing prediction method;

[0148] Calculate the required compensation capacity according to the reactive power shortage prediction value, and decompose the compensation capacity into grades to generate a graded compensation instruction sequence; the compensation capacity is the reactive power required by the reactive power compensation device;

[0149] According to the hierarchical compensation instruction sequence and the operating status of the equipment, the output limit of the reactive power compensation equipment is adjusted to dynamically compensate for the reactive power shortage of the power grid.

[0150] Specifically, this embodiment sets a sampling period according to the stability of the power grid and the response speed of the reactive compensation device, collects various operating status parameters and reactive power data of the reactive compensation device by using sensors, obtains the device operating status and reactive power data of the reactive compensation device, pre-processes the collected device operating status and reactive power data, such as denoising and filtering, to improve data quality, obtains pre-processed device operating status and pre-processed reactive power data, and uses a recursive least squares algorithm (RLS) to fit the pre-processed device operating status and pre-processed reactive power data to obtain the reactive power shortage value and reactive power shortage change rate of the current power grid. The RLS algorithm can update the model parameters online to adapt to the dynamic changes of the power grid, and at the same time records the time point when the reactive power shortage value first appears and the time point when it last appears, and calculates the duration of the reactive power shortage according to the difference between the time point when the reactive power shortage value first appears and the time point when it last appears.

[0151] Then, this embodiment uses the exponential smoothing prediction method (ESP) to build an exponential smoothing prediction model based on the reactive power shortage value, the reactive power shortage change rate and the duration length, and uses the exponential smoothing prediction model to predict the reactive power shortage to obtain the reactive power shortage prediction value in the future period of time. According to the reactive power shortage prediction value, the required compensation capacity (that is, the reactive power required by the reactive power compensation device) is calculated, and the compensation capacity is hierarchically decomposed according to rules such as time or priority to generate a hierarchical compensation instruction sequence. Each instruction sequence contains a series of specific compensation capacities for guiding the output adjustment of the reactive power compensation device. This embodiment can achieve hierarchical decomposition of compensation capacity by setting different compensation levels and corresponding compensation capacities to adapt to different scales. Reactive power shortage. Then, this embodiment executes the compensation instructions in sequence according to the order of the hierarchical compensation instruction sequence, and adjusts the output limit of the reactive compensation device according to the compensation instruction. For example, when the power grid has a reactive power shortage, the output limit of the reactive compensation device is increased to provide additional reactive power; when the power grid has an excess of reactive power, the output limit of the reactive compensation device is reduced to reduce reactive output. During the adjustment process, the operating status and reactive power data of the reactive compensation device are monitored in real time, and the output limit is fine-tuned according to the feedback results to achieve dynamic adjustment of the output limit of the reactive compensation device, thereby effectively compensating for the reactive power shortage of the power grid and ensuring that the reactive compensation device can dynamically adjust the output limit according to the actual needs of the power grid, thereby improving the stability and power quality of the power grid.

[0152] An embodiment of the present invention provides a method for optimizing reactive power control of a regional power grid. The method collects key characteristic parameters of reactive compensation equipment in a regional power grid in real time, and establishes a dynamic response matrix based on the key characteristic parameters; dynamically tracks the reactive power flow of the power grid based on the dynamic response matrix and the power flow operation status data of the regional power grid lines to obtain the reactive power demand change trend within a preset time period in the future; determines the target output adjustment value of each reactive compensation equipment based on the reactive power demand change trend and the key characteristic parameters; generates an output adjustment control instruction based on the target output adjustment value of each reactive compensation equipment; adjusts the reactive output of each reactive compensation equipment in real time based on the output adjustment control instruction, and dynamically adjusts the output limit of the reactive compensation equipment based on the equipment operation status and reactive power data of the reactive compensation equipment during the reactive output adjustment process of the reactive compensation equipment. Compared with the existing technology, this method adjusts the target output by establishing technologies such as a dynamic response matrix, and dynamically adjusts the output limits of different reactive compensation equipment, thereby achieving precise control and optimal regulation of the output of reactive compensation equipment, improving reactive compensation efficiency, enhancing grid stability and voltage support capabilities, while reducing equipment losses and operation and maintenance costs. It can effectively respond to the complex and changeable reactive demand problems brought about by the access of renewable energy, and improve the overall reactive optimization efficiency of the power grid.

[0153] It should be noted that the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0154] In one embodiment, Figure 2 As shown, an embodiment of the present invention provides a regional power grid reactive power optimization control system, the system comprising:

[0155] The data acquisition module 101 is used to collect key characteristic parameters of reactive power compensation equipment in the regional power grid in real time, and establish a dynamic response matrix according to the key characteristic parameters;

[0156] The power flow tracking module 102 is used to dynamically track the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line, and obtain the reactive power demand change trend within a preset time period in the future;

[0157] The output analysis module 103 is used to determine the target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters;

[0158] The instruction generation module 104 is used to generate an output regulation control instruction according to the target output regulation value of each reactive power compensation device; the output regulation control instruction includes a control mode, an output limit value and an execution cycle;

[0159] The output regulation module 105 is used to regulate the reactive output of each reactive compensation device in real time according to the output regulation control instruction, and dynamically adjust the output limit of the reactive compensation device according to the device operating status and reactive power data of the reactive compensation device during the reactive output regulation process of the reactive compensation device.

[0160] For the specific definition of a regional power grid reactive power optimization control system, please refer to the above-mentioned definition of a regional power grid reactive power optimization control method, which will not be repeated here. A person of ordinary skill in the art will appreciate that the various modules and steps described in conjunction with the embodiments disclosed in this application can be implemented in hardware, software, or a combination of both. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0161] An embodiment of the present invention provides a regional power grid reactive power optimization control system, wherein the system collects key characteristic parameters of reactive compensation equipment in a regional power grid in real time through a data acquisition module, and establishes a dynamic response matrix according to the key characteristic parameters; a power flow tracking module dynamically tracks the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line, and obtains the reactive power demand change trend within a preset time period in the future; an output analysis module determines a target output adjustment value of each reactive compensation equipment according to the reactive power demand change trend and the key characteristic parameters; an instruction generation module generates an output adjustment control instruction according to the target output adjustment value of each reactive compensation equipment; an output adjustment module adjusts the reactive output of each reactive compensation equipment in real time according to the output adjustment control instruction, and dynamically adjusts the output limit of the reactive compensation equipment according to the equipment operation status and reactive power data of the reactive compensation equipment during the reactive output adjustment process of the reactive compensation equipment. Compared with the existing technology, this system establishes a dynamic response matrix and other technologies to adjust the target output, and dynamically adjusts the output limits of different reactive compensation equipment, thereby realizing precise control and optimal regulation of the reactive compensation equipment output, improving reactive compensation efficiency, enhancing grid stability and voltage support capabilities, while reducing equipment losses and operation and maintenance costs. It can effectively respond to the complex and changeable reactive demand problems brought about by the access of renewable energy, and improve the overall reactive optimization efficiency of the grid.

[0162] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A method for optimizing reactive power control in a regional power grid, characterized in that: The following steps are involved: Real-time collection of key characteristic parameters of reactive power compensation equipment in the regional power grid, and establishment of a dynamic response matrix based on the key characteristic parameters; Dynamically track the reactive power flow of the power grid based on the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within the future preset time period; Determining a target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters; Generate output regulation control instructions according to the target output regulation value of each reactive power compensation device; Adjust the reactive output of each reactive compensation device in real time according to the output adjustment control instruction, and dynamically adjust the output limit of the reactive compensation device according to the device operation status and reactive power data of the reactive compensation device during the reactive output adjustment process of the reactive compensation device; The step of establishing a dynamic response matrix according to the key characteristic parameters includes: Arranging the key characteristic parameters in a predetermined order to construct a characteristic parameter vector; Calculate the sliding variance value of the characteristic parameter vector in different sliding windows and construct the fluctuation characteristic matrix; The fluctuation characteristic matrix is ​​processed by using an exponentially weighted moving average method to generate a prediction sequence; Calculating a root mean square error of the prediction sequence, and determining a steady-state interval according to the root mean square error; Select the characteristic submatrix corresponding to the steady-state interval from the fluctuation characteristic matrix; Performing singular value decomposition on the characteristic submatrix, and selecting eigenvectors corresponding to the first several largest singular values ​​to construct a stable subspace; In the stable subspace, the stability index value corresponding to each singular value is calculated. If the stability index value is less than a preset stability threshold, the current characteristic submatrix is ​​determined as the dynamic response matrix of the reactive compensation device.

2. A method for optimizing reactive power control in a regional power grid according to claim 1, characterized in that: The step of real-time acquisition of key characteristic parameters of reactive power compensation equipment in the regional power grid comprises: Collecting compensation voltage and current signals of reactive power compensation equipment from the regional power grid in real time, and calculating the actual operating capacity value of the reactive power compensation equipment based on the compensation voltage and current signals; Constructing a voltage response curve of a reactive power compensation device according to the actual operating capacity value, and performing piecewise linear fitting on the voltage response curve using a sliding time window to obtain a fitting curve; According to the slope change rate of the fitting curve, the dynamic response time point is identified; Acquire an actual value of a voltage variation of the reactive power compensation device, and analyze the actual value of the voltage variation by using a recursive least square method with a forgetting factor to obtain a voltage variation prediction value; Calculating the adjustment accuracy value of the reactive power compensation device according to the difference between the actual value of the voltage change and the predicted value of the voltage change; The key characteristic parameters of the reactive compensation equipment are generated according to the actual operating capacity value, dynamic response time point, dynamic response dead zone range value and adjustment accuracy value of the reactive compensation equipment; wherein the key characteristic parameters include available capacity, dynamic response time, adjustment accuracy value and dynamic response dead zone.

3. A method for optimizing reactive power control of a regional power grid according to claim 1, characterized in that: After the step of establishing a dynamic response matrix according to the key characteristic parameters, the following steps are further included: Generate an initial response prediction curve of the reactive compensation device according to the dynamic response matrix, and iteratively optimize the initial response prediction curve using a gradient descent algorithm to minimize the difference between the initial response prediction curve and the actual response, so as to obtain an optimized prediction curve; Performing parameter correction on the fluctuation characteristic matrix according to the optimized prediction curve to obtain a corrected fluctuation characteristic matrix; The dynamic response matrix of the reactive power compensation device is updated according to the modified fluctuation characteristic matrix.

4. A method for optimizing reactive power control in a regional power grid according to claim 1, characterized in that: The step of dynamically tracking the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line to obtain the reactive power demand change trend within the future preset time period includes: Analyze the dynamic response characteristics of the reactive compensation equipment according to the dynamic response matrix, and construct a capacity attenuation characteristic curve of the reactive compensation equipment that changes with time; Calculate the difference between the reactive capacity and the rated capacity of each reactive compensation device in the current state according to the capacity attenuation characteristic curve to obtain a reactive shortage data set; Collecting voltage amplitude data of the power grid branch, and smoothing the voltage amplitude data using the Kalman filter method to obtain smoothed voltage amplitude data; Integrating the smoothed voltage amplitude data and the reactive power shortage data set with the topological structure information of the power grid branch to obtain an operation state vector of the power grid branch; Extracting reactive power flow components from the operation state vector of the power grid branch, dynamically predicting the reactive power flow components using an adaptive exponential smoothing method, and obtaining reactive power flow component prediction results; According to the reactive power flow component prediction result and the impedance parameter of the power grid branch, reactive power flow transmission data on the power grid branch is obtained through power flow calculation; The reactive power flow transmission data is fitted by using cubic polynomial fitting to predict the reactive power demand change trend of the regional power grid within a preset time period in the future.

5. A method for optimizing reactive power control in a regional power grid according to claim 2, characterized in that: The step of determining the target output adjustment value of each reactive compensation device according to the reactive demand change trend and the key characteristic parameters comprises: According to the trend of reactive power demand, the reactive power demand of the power grid at different time points is extracted at preset fixed time intervals; Quantifying the reactive power demand according to the regulation accuracy value of the reactive power compensation device to obtain the expected regulation step length of the reactive power compensation device at different time points; Generate a response curve of the reactive compensation device under reactive demand changes according to the expected adjustment step length of the reactive compensation device at different time points; Each time point on the response curve is traversed, and a target output adjustment value is obtained according to the response curve and the actual adjustment capability of the reactive power compensation device at the current time point.

6. A method for optimizing reactive power control in a regional power grid according to claim 5, characterized in that: The step of generating a response curve of the reactive compensation device under reactive demand changes according to the expected adjustment step length of the reactive compensation device at different time points comprises: According to the rated power of the reactive power compensation equipment, the switching loss and conduction loss corresponding to the unit compensation amount are calculated; Performing a weighted summation of the switching loss and the conduction loss to obtain a compensation loss coefficient; A response curve of the reactive power compensation device under reactive power demand changes is generated according to the compensation loss coefficient and the expected adjustment step size.

7. A method for optimizing reactive power control in a regional power grid according to claim 1, characterized in that: The step of adjusting the reactive output of each reactive compensation device in real time according to the output adjustment control instruction comprises: In response to the received output regulation control instruction, a time difference between the execution time of the output regulation control instruction and the current system time is calculated using a network time protocol; According to the time difference, the execution delay of the output regulation control instruction is predicted by the Kalman filter algorithm; According to the instruction, the real-time operating parameters of each reactive compensation device are collected in a delayed manner, and the actual reactive output value of each reactive compensation device at the current moment is calculated based on the real-time operating parameters; According to the deviation between the actual reactive power output value of each reactive power compensation device and the preset target output value, the reactive power output adjustment control value is calculated by using a proportional integral controller; The reactive output regulation control value is smoothed by using a cubic spline curve interpolation method to obtain a smooth regulation curve; Extract reactive power output data at each time point from the smooth adjustment curve, and generate a feedback information packet according to the reactive power output data and the instruction execution delay; The reactive output of the reactive compensation equipment is adjusted in real time according to the feedback information package until the reactive output of each reactive compensation equipment stably reaches the target output value.

8. A method for optimizing reactive power control in a regional power grid according to claim 1, characterized in that: In the reactive output regulation process of the reactive compensation device, the step of dynamically adjusting the output limit of the reactive compensation device according to the device operation status and reactive power data of the reactive compensation device comprises: Acquire the equipment operation status and reactive power data of reactive compensation equipment in real time at a preset sampling period; According to the reactive power data and the operating status of the equipment, a recursive least squares algorithm is used to obtain the reactive power shortage value and reactive power shortage change rate of the current power grid; Determine the duration of reactive power shortage according to the time point when the reactive power shortage value occurs; According to the reactive power shortage value, the reactive power shortage change rate and the duration of the reactive power shortage, a reactive power shortage prediction value is obtained by using an exponential smoothing prediction method; Calculate the required compensation capacity according to the reactive power shortage prediction value, and decompose the compensation capacity into grades to generate a graded compensation instruction sequence; the compensation capacity is the reactive power required by the reactive power compensation device; According to the hierarchical compensation instruction sequence and the operating status of the equipment, the output limit of the reactive power compensation equipment is adjusted to dynamically compensate for the reactive power shortage of the power grid.

9. A regional power grid reactive power optimization control system, characterized in that: The system comprises: A data acquisition module is used to collect key characteristic parameters of reactive power compensation equipment in a regional power grid in real time, and to establish a dynamic response matrix based on the key characteristic parameters; The power flow tracking module is used to dynamically track the reactive power flow of the power grid according to the dynamic response matrix and the power flow operation status data of the regional power grid line, and obtain the reactive power demand change trend within the future preset time period; An output analysis module, used to determine the target output adjustment value of each reactive power compensation device according to the reactive power demand change trend and the key characteristic parameters; An instruction generation module is used to generate an output regulation control instruction according to the target output regulation value of each reactive power compensation device; An output regulation module is used to regulate the reactive output of each reactive compensation device in real time according to the output regulation control instruction, and dynamically adjust the output limit of the reactive compensation device according to the device operation status and reactive power data of the reactive compensation device during the reactive output regulation process of the reactive compensation device; The step of establishing a dynamic response matrix according to the key characteristic parameters specifically includes: Arranging the key characteristic parameters in a predetermined order to construct a characteristic parameter vector; Calculate the sliding variance value of the characteristic parameter vector in different sliding windows and construct the fluctuation characteristic matrix; The fluctuation characteristic matrix is ​​processed by using an exponentially weighted moving average method to generate a prediction sequence; Calculating a root mean square error of the prediction sequence, and determining a steady-state interval according to the root mean square error; Select the characteristic submatrix corresponding to the steady-state interval from the fluctuation characteristic matrix; Performing singular value decomposition on the characteristic submatrix, and selecting eigenvectors corresponding to the first several largest singular values ​​to construct a stable subspace; In the stable subspace, the stability index value corresponding to each singular value is calculated. If the stability index value is less than a preset stability threshold, the current characteristic submatrix is ​​determined as the dynamic response matrix of the reactive compensation device.

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