Converter transformer on-load tap-changer control system and method

Abstract

The invention discloses a converter transformer on-load tap-changer control system and method, and relates to the technical field of converter transformer tap-changer control, and the method comprises the following steps: monitoring the key operation parameters of a converter transformer at all moments in real time through a high-precision sensor and a data collection system, and carrying out the real-time monitoring of the key operation parameters of the converter transformer at all moments based on the collected operation parameter data; constructing a time sequence model of the operating state of the converter transformer, describing a rule of operating parameters changing along with time through the model, and capturing dynamic characteristics of the operating state; and predicting the change trend of the operation state of the converter transformer in a period of time in the future by using the constructed time sequence model. Through the time sequence model and the dynamic programming optimization method, the switching opportunity of the tap of the converter transformer is reasonably arranged, operation and mechanical abrasion are reduced, and the service life of equipment is prolonged. Meanwhile, a power loss quantitative index is introduced into the cost function, a switching strategy is optimized, a scheme with the minimum power loss is screened out, and the economical efficiency and stability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of converter transformer tap changer control, and in particular to a converter transformer on-load tap changer control system and method. Background Art

[0002] In the prior art, the specific principle of converter transformer on-load tap changer (OLTC) control is usually based on a closed-loop feedback control system. By real-time monitoring of the transformer's output voltage and load current, when it is detected that the voltage deviates from the set target value (for example, higher or lower than the set threshold range), the control system triggers the tap changer to switch to the appropriate tap to adjust the transformer's output voltage to ensure that the voltage is stable within a predetermined range.

[0003] The prior art has the following deficiencies:

[0004] In actual use, the on-load tap changer (OLTC) control system of the converter transformer in the prior art often lacks the ability to predict future changes in operating status, and mainly relies on simple feedback control based on real-time monitored voltage and load data. This approach makes it difficult to fully optimize the switching strategy of the tap changer, which can easily lead to frequent switching, increased mechanical wear of the equipment, and shortened service life. In addition, improper switching timing may lead to increased power loss and reduce the overall efficiency and economy of the system. These problems are particularly serious when load fluctuations are frequent or grid conditions are complex, which may endanger the stability of the power system and affect the long-term reliability of the equipment.

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

[0006] The purpose of the present invention is to provide a control system and method for an on-load tap changer of a converter transformer. By constructing a time series model and a dynamic programming optimization method, the tap switching timing of the converter transformer can be predicted in advance and reasonably arranged, thereby reducing unnecessary operations, reducing mechanical wear, extending equipment life, and improving the long-term reliability of the system. At the same time, by introducing a power loss quantification index into the cost function and globally optimizing the switching strategy, a switching scheme with the minimum power loss is screened out, thereby improving the system economy and energy efficiency, and enhancing the stability of the power system, so as to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a method for controlling an on-load tap changer of a converter transformer, comprising the following steps:

[0008] Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status.

[0009] The constructed time series model is used to predict the changing trend of the operating status of the converter transformer in the future.

[0010] Determine the best time to switch the tap of the converter transformer according to the predicted trend of operation status change;

[0011] For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost;

[0012] Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss.

[0013] The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment.

[0014] According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions.

[0015] Preferably, based on the collected converter transformer operating parameter data, the specific steps of constructing the time series model of the converter transformer operating state are as follows:

[0016] Select a high-precision sensor system suitable for monitoring key parameters of converter transformers;

[0017] Build a data acquisition and transmission system to capture the dynamic changes of converter transformer operating status in real time;

[0018] After the data is transmitted to the central control system, the data is monitored and pre-processed in real time;

[0019] After the preprocessing is completed, a time series model is constructed based on the cleaned data. The time series model is used to describe the change pattern of key operating parameters of the converter transformer over time and capture the dynamic characteristics thereof.

[0020] Preferably, the specific steps of determining the optimal time point for switching the tap of the converter transformer are as follows:

[0021] Use the constructed time series model to make multi-step forward predictions of the operating status in the future. t represents the key operating parameter, and its predicted value for the next k steps is expressed as: In the formula, is the predicted value at time point t+k, g(·) is the prediction function based on the time series model, θ is the model parameter set, n is the length of the historical data window, and k is the index of the time step;

[0022] Based on the predicted operating state value, the predicted state change rate at each time point is calculated to capture the moment of drastic change of the future operating state, and the predicted state change rate V is defined as t+k for:

[0023] ,

[0024] Where p is the nonlinear expansion exponent, and λ is the time attenuation factor;

[0025] Calculate the predicted state change acceleration A t+k , the predicted state change acceleration can capture more subtle dynamic change characteristics, and the calculation expression is:

[0026] ,

[0027] Where Δt is the time step, A t+k represents the predicted state change acceleration at time point t+k;

[0028] Combine the predicted state change rate and predicted state change acceleration to construct the discriminant function Q of the key time point t+k , the expression of the discriminant function is:

[0029] ,

[0030] In the formula, It represents the maximum value of the product of the predicted state change rate and the predicted state change acceleration at all future time points t+j. j represents the time point index, which is used to traverse each future time point. β is the weight coefficient of the predicted state change acceleration. Function Q t+k The state change characteristics at each time point are standardized;

[0031] Through the discriminant function Q t+k The maximum value of is used to determine the optimal switching time point. The calculation expression for the optimal switching time point is: In the formula, t * Indicates the optimal switching time point.

[0032] Preferably, the power loss difference at each determined switching time point is defined as the switching cost, and the specific steps are as follows:

[0033] Before the switching time point is determined, the power loss P under the current tap position is obtained. pre , the power loss is calculated by real-time monitoring of the electrical parameters of the system operation, and the calculation expression is: In the formula, I t is the current at the current tap position, R pre is the resistance of the current tap position, V t is the voltage at the current tap position, cos(φ pre ) is the power factor of the current tap position;

[0034] Predict the power loss R after switching to the new tap position post , after switching, the power loss after switching to the new tap position is calculated as: In the formula, R post and cos(φ post ) is the resistance and power factor corresponding to the new tap position after switching, I t+k and V t+k are the current and voltage corresponding to the new tap position after switching;

[0035] After obtaining the power loss data before and after the switching, the difference between the two is calculated to quantify the impact of the switching operation. The power loss difference ΔP is expressed as: ΔP = P post -P pre ;

[0036] Finally, the calculated power loss difference ΔP is defined as the switching cost.

[0037] Preferably, a cost function is constructed to evaluate the power loss at each switching time point, and the specific steps are:

[0038] Define the power loss function P for each switching time point t+k t+k , power loss function P t+k It represents the power loss of the converter transformer in the future time series. Considering the changes of current, voltage, resistance and power factor, the power loss function P t+k The expression is: In the formula, I t is the current at time t, R t is the resistance at time t, V t is the voltage at time t, cos(φ t ) is the power factor at time t;

[0039] Calculate the power loss difference ΔP before and after a specific switching time point t+k t+k , this difference directly reflects the impact of the switching operation on the system energy efficiency, and the calculation expression is: ΔP t+k =P post，t+l -P pre，t+k , where P pre，t+k is the power loss before switching, P pre，t+k is the power loss after switching.

[0040] Preferably, the power loss difference ΔP t+k Introducing the cost function C t+k , the power loss at each switching time point is evaluated, and the expression of the cost function is:

[0041] ,

[0042] Where, T t+k is the time weight factor, which is used to adjust the importance of the switching time point, and α is an exponential parameter that controls the degree of nonlinearity of the function;

[0043] Using the defined cost function C t+k , perform cost evaluation on all switching time points t+k, specifically traversing each existing switching time point in the future time period and calculating the corresponding cost value;

[0044] The cost values ​​generated at all switching time points are used to create a data set, and the cost values ​​in the data set are sorted in order, and the time point with the smallest cost value is selected from all switching time points as the optimal switching time.

[0045] Preferably, a dynamic programming optimization method is used to solve the cost function to obtain the optimal tap switching strategy, and the specific steps are:

[0046] First, define the state transfer function S(t+k,u), where u represents the tap switching operation at time point t+k, S(t+k,u) describes the current state transferred to the next time point by selecting u, and the state transfer function is expressed as: S(t+k,u)=P t+k +f(S(t+k-1,u-1)), where P t+k is the power loss at time point t+k, and the function f(S(t+k-1,u-1)) represents the influence of the state at the previous time point on the current state;

[0047] In dynamic programming, the stage cost function C(t+k,u) is constructed to represent the power loss cost when operation u is selected at time point t+k. The construction expression of the stage cost function C(t+k,u) is: C(t+k,u)=r(S(t+k,u),u), where r(S,u) is the functional relationship between power loss and operation, and represents the total power loss after selecting u.

[0048] Preferably, the idea of ​​dynamic programming is used to recursively solve the optimal sub-problem at each time point, and the optimal value function M(t+k) is defined as the minimum cumulative power loss after the time point t+k, which is obtained by recursive calculation. The calculation expression is: M(t+k)=min u∈U {C(t+k,u)+M(t+k+1)}, where U represents the set of all existing operations;

[0049] In dynamic programming, boundary conditions are used to determine the starting point or end point of the recursive calculation. The optimal value function M(t+k) at the last time point t+N is set as the known final value. Here, the optimal value function M(t+k) is defined as: M(t+k)=C(t+k, u * ), where u * is the operation selected at the last time point, and N represents the last time step in the prediction time range;

[0050] Through the reverse backtracking method, we start from the boundary conditions and backtrack step by step to build the optimal switching strategy at each time point. The optimal strategy Φ(t+k) is defined as the optimal operation selected at each time point. The specific expression is: Φ(t+k)=argmin u∈U {C(t+k,u)+M(t+k+1)}, the optimal strategy Φ(t+k) on the entire time series is obtained by back-calculation, and this strategy is applied in actual operation for tap switching to ensure that the power loss of the system is minimized at every moment.

[0051] Preferably, after the optimal tap switching strategy is obtained through dynamic programming optimization, the specific process of real-time control of the switching action of the on-load tap changer is as follows:

[0052] First, according to the switching time point and corresponding operation determined in the optimal strategy, specific operation instructions are generated;

[0053] The control system then executes these instructions through the actuators to ensure that the taps are switched at the specified time.

[0054] A converter transformer on-load tap changer control system includes a data acquisition and model building module, a state prediction module, an optimal switching timing determination module, a switching cost calculation module, a cost function construction and evaluation module, a dynamic programming optimization module and a real-time control execution module;

[0055] Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status.

[0056] The constructed time series model is used to predict the changing trend of the operating status of the converter transformer in the future.

[0057] Determine the best time to switch the tap of the converter transformer according to the predicted trend of operation status change;

[0058] For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost;

[0059] Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss.

[0060] The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment.

[0061] According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions.

[0062] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0063] The present invention uses the above-mentioned converter transformer on-load tap changer control method to construct a time series model and utilize a dynamic programming optimization method to predict and reasonably arrange the switching timing in advance, reduce unnecessary operations, reduce mechanical wear, extend the service life of the equipment, and improve the long-term reliability of the system.

[0064] The present invention optimizes the switching strategy, introduces a quantitative index of power loss into the cost function, and uses dynamic programming to globally optimize the switching strategy, so as to screen out the switching scheme with the minimum power loss, so that each tap switching can be carried out with the minimum power loss, thereby improving the economy and energy efficiency of the system operation and enhancing the stability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0066] Figure 1 The present invention is a method flow chart of a method for controlling an on-load tap changer of a converter transformer.

[0067] Figure 2 The present invention is a module schematic diagram of a converter transformer on-load tap changer control system. DETAILED DESCRIPTION

[0068] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0069] The present invention provides Figure 1 A converter transformer on-load tap changer control method is shown, comprising the following steps:

[0070] Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status.

[0071] Based on the collected converter transformer operating parameter data, the specific steps of constructing the time series model of the converter transformer operating status are as follows:

[0072] Select a high-precision sensor system suitable for monitoring key parameters of converter transformers;

[0073] The sensors in the high-precision sensor system should be able to measure and record key operating parameters including voltage, current, temperature, frequency, power factor, etc. in real time. The selection of sensors needs to consider measurement accuracy, response speed and anti-interference ability to ensure accurate and stable data under various working conditions. The installation location of the sensor is also crucial and should be as close to key components as possible to capture subtle changes in operating status in real time. In addition, in order to ensure data integrity, the sensor system should be seamlessly integrated with the transformer's control and monitoring system and have a redundant design to deal with possible equipment failures.

[0074] Build a data acquisition and transmission system to capture the dynamic changes of converter transformer operating status in real time;

[0075] The core of the system is the data acquisition device (such as a data logger or PLC), which needs to have a high sampling rate and large-capacity data storage capability to capture the parameter data collected by the sensor in real time. The data acquisition system should set a reasonable sampling frequency to ensure that it can capture the dynamic changes in the operating status of the converter transformer while avoiding data redundancy. The collected data is transmitted to the central control system or cloud server in real time via a wired or wireless network for centralized processing and analysis. The integrity and security of the data should be ensured during the data transmission process, and encryption technology and data verification mechanisms should be used to prevent data loss or tampering.

[0076] After the data is transmitted to the central control system, the data is monitored and pre-processed in real time;

[0077] Real-time monitoring involves continuous tracking of sensor data to detect possible anomalies or faults. Preprocessing includes steps such as data cleaning, denoising, and normalization to ensure that the data input into the model is accurate and consistent. For example, it may be necessary to filter out abnormal data points due to sensor noise or faults, and normalize different types of data for unified analysis. At this stage, the preprocessed data can also be subjected to simple statistical analysis, such as calculating the mean value, standard deviation, etc., to gain a preliminary understanding of the operating status and trend of the converter transformer.

[0078] After the preprocessing is completed, a time series model is constructed based on the cleaned data. The time series model is used to describe the change pattern of the key operating parameters of the converter transformer over time and capture the dynamic characteristics thereof.

[0079] Common time series modeling methods include ARIMA model, long short-term memory network (LSTM), autoregressive conditional heteroskedasticity model (GARCH), etc. The choice of model should be based on the characteristics of the data and specific analysis requirements. When building the model, it is necessary to train the historical data and tune the model parameters to improve the prediction accuracy and generalization ability of the model. In this way, the time series model can effectively identify the periodic trends, sudden anomalies and long-term evolution in the operating status of the converter transformer.

[0080] The constructed time series model is used to predict the operating status change trend of the converter transformer in the future, and the optimal time point for switching the tap of the converter transformer is determined according to the predicted operating status change trend;

[0081] The specific steps for determining the optimal time point for switching the converter transformer tap are as follows:

[0082] Use the constructed time series model (such as LSTM, GRU or extended Kalman filter EKF) to make multi-step forward predictions of the operating status in the future. t represents key operating parameters (such as voltage, load, etc.), and its predicted value for the next k steps is expressed as: In the formula, is the predicted value at time point t+k, g(·) is the prediction function based on the time series model, θ is the model parameter set, n is the length of the historical data window, and k is the index of the time step;

[0083] The goal of this step is to generate parameter predictions at multiple time points in the future for subsequent analysis.

[0084] Based on the predicted operating state value, the predicted state change rate at each time point is calculated to capture the moment of drastic change of the future operating state, and the predicted state change rate V is defined as t+k for:

[0085] ,

[0086] Where p is the nonlinear expansion exponent, and λ is the time attenuation factor;

[0087] The nonlinear expansion exponent p is an exponential factor used to increase or decrease the magnitude of changes in the prediction parameters at different time points. It is used to introduce nonlinear effects when calculating the predicted state change rate, so that the impact of parameter changes can be amplified or reduced according to specific needs. By adjusting the value of p, the sensitivity of state changes can be flexibly controlled.

[0088] When p>1, larger changes will be further amplified, which is suitable for situations where dramatic fluctuations need to be emphasized.

[0089] When p<1 and p>0, smaller changes will be amplified and larger changes will be compressed. This setting is suitable for smoothing drastic changes and enhancing the response to small changes.

[0090] When p=1, the formula remains linear and the change is proportional to the change in the original data.

[0091] The specific value can be set according to the operating characteristics and actual needs of the system. For example, when you need to be particularly sensitive to sharp fluctuations, you can choose p>1; when you need to smooth sharp fluctuations, you can choose p<1. By adjusting p, you can flexibly respond to different types of operating state changes.

[0092] The predicted state change rate is used to measure the state change rate at each future time point. A high rate means that the state of the system will fluctuate dramatically in the future and tap switching may be required.

[0093] In order to further quantify the severity of the state change, the predicted state change acceleration A is calculated t+k , the predicted state change acceleration can capture more subtle dynamic change characteristics, and the calculation expression is:

[0094] ,

[0095] Where Δt is the time step, A t+k represents the predicted state change acceleration at time point t+k;

[0096] By calculating the predicted acceleration of state change, we can identify the time points where drastic changes may occur, and these points need to be given special consideration.

[0097] Combine the predicted state change rate and predicted state change acceleration to construct the discriminant function Q of the key time point t+k , the expression of the discriminant function is:

[0098] ,

[0099] In the formula, It represents the maximum value of the product of the predicted state change rate and the predicted state change acceleration at all future time points t+j. j represents the time point index, which is used to traverse each future time point. β is the weight coefficient of the predicted state change acceleration. Function Q t+k The state change characteristics of each time point are standardized. Through this function, the severity of changes at future time points can be ranked. The time point corresponding to the maximum value is the best switching time.

[0100] Through the discriminant function Q t+kThe maximum value of is used to determine the optimal switching time point. The calculation expression for the optimal switching time point is: Where, t * Indicates the optimal switching time point;

[0101] This step directly selects the time point with the largest discriminant function value as the best time to switch the tap, ensuring that the tap is switched at the most drastic and appropriate moment of state change, thereby optimizing the stability and operation efficiency of the system.

[0102] For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost;

[0103] The power loss difference at each determined switching time point is defined as the switching cost. The specific steps are as follows:

[0104] Before the switching time point is determined, the power loss P under the current tap position is obtained. pre , the power loss is calculated by real-time monitoring of the electrical parameters (such as voltage, current, and load) of the system operation. The calculation expression is: In the formula, I t is the current at the current tap position, R pre is the resistance of the current tap position, V t is the voltage at the current tap position, cos(φ pre ) is the power factor of the current tap position;

[0105] The core of this step is to accurately capture and calculate the power loss of the current tap position, laying the foundation for the subsequent switching cost calculation.

[0106] Predict the power loss P after switching to the new tap position post After switching, due to the change in the tap position, electrical parameters such as resistance and power factor will also change accordingly. At this time, the calculation expression for the power loss after switching to the new tap position is: In the formula, R post and cos(φ post ) is the resistance and power factor corresponding to the new tap position after switching, I t+k and V t+k are the current and voltage corresponding to the new tap position after switching;

[0107] In order to accurately predict the changes in these parameters, existing time series models can be used or calculations can be performed based on the physical characteristics of the system. The goal of this step is to obtain the power loss data of the new tap position by analyzing the operating status after switching.

[0108] After obtaining the power loss data before and after the switching, the difference between the two is calculated to quantify the impact of the switching operation. The power loss difference ΔP is expressed as: ΔP = P post -P pre ;

[0109] The power loss difference ΔP directly reflects the impact of the switching operation on the system energy efficiency. If ΔP is positive, it means that the power loss increases after the switching, and vice versa. This calculation can not only quantify the immediate impact of the switching, but also provide a basis for defining the switching cost in the next step.

[0110] Finally, the calculated power loss difference ΔP is defined as the switching cost C switch , the expression defined is: C switch =|ΔP|;

[0111] The switching cost is expressed as the absolute change in power loss and is a measure of the impact of the switching operation on energy consumption.

[0112] Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss.

[0113] Define the power loss function P for each switching time point t+k t+k , power loss function P t+k It represents the power loss of the converter transformer in the future time series. Considering the changes of current, voltage, resistance and power factor, the power loss function P t+k The expression is: In the formula, I t is the current at time t, R t is the resistance at time t, V t is the voltage at time t, cos(φ t ) is the power factor at time t;

[0114] This integral formula represents the accumulated power loss in the time range from t to t+k. By calculating P at different time points t+k , you can understand the power loss at each time point.

[0115] Calculate the power loss difference ΔP before and after a specific switching time point t+k t+k , this difference directly reflects the impact of the switching operation on the system energy efficiency, and the calculation expression is: ΔP t+k =P post，t+l -P pre，t+k , where Ppre，t+k is the power loss before switching, P pre，t+k is the power loss after switching;

[0116] By calculating the power loss difference ΔP t+k , the power loss change caused by the switching operation at each time point can be quantified.

[0117] The power loss difference ΔP t+k Introducing the cost function C t+k , the power loss at each switching time point is evaluated, and the expression of the cost function is:

[0118] ,

[0119] Where, T t+k It is the time weight factor, which is used to adjust the importance of the switching time point. Its function is to highlight or weaken the relative importance of certain time points by assigning different weights to different time points when calculating the cost function. t+k , can better optimize the selection of switching time points to ensure that switching is performed at the most appropriate time, thereby improving the overall operating efficiency and stability of the system. The specific setting criteria of the time weight factor are usually based on the operating characteristics and strategic goals of the system. For example, the time weight factor T can be set based on historical operating data, load change patterns, equipment aging, or power grid fluctuation characteristics. t+k . If the power demand or load at certain time points fluctuates frequently, higher weights can be given to these time points, so that tap switching can be prioritized at these moments. On the contrary, for time periods when the load is stable or the system operation status is stable, lower weights can be set to reduce unnecessary switching operations. Through such settings, the switching strategy can be optimized to improve the efficiency and reliability of the system. α is an exponential parameter of the nonlinearity of the control function. The cost function aims to minimize the power loss difference and consider the priority of the switching time point at the same time.

[0120] Using the defined cost function C t+k , perform cost evaluation on all switching time points t+k. Specifically, it is necessary to traverse each existing switching time point in the future time period and calculate the corresponding cost value;

[0121] The purpose of this step is to systematically evaluate the power loss at all time points so as to select the time point with the least cost in the subsequent steps.

[0122] The cost values ​​generated at all switching time points are used to establish a data set, and the cost values ​​in the data set are sorted in order, and the time point with the smallest cost value is selected from all switching time points as the optimal switching time;

[0123] This selection criterion ensures that the system performs tap switching with minimum power loss and optimal energy efficiency. t+k , the system can switch at the appropriate time point, thereby optimizing power loss and improving operating efficiency.

[0124] The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment.

[0125] The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. The specific steps are as follows:

[0126] First, define the state transfer function S(t+k,u), where u represents the tap switching operation at time point t+k, S(t+k,u) describes the current state transferred to the next time point by selecting u, and the state transfer function is expressed as: S(t+k,u)=P t+k +f(S(t+k-1,u-1)), where P t+k is the power loss at time point t+k, and the function f(S(t+k-1,u-1)) represents the influence of the state at the previous time point on the current state;

[0127] The function f(S(t+k-1, u-1)) reflects how the power loss at time point t+k is affected by the state transfer or operation decision at the previous time point t+k-1. The determination of the function f(S(t+k-1, u-1)) is usually based on the physical characteristics and dynamic behavior of the system. For example, in the case of a converter transformer, the function f(S(t+k-1, u-1)) can be modeled based on the rate of change of current, voltage, adjustment of power factor, and system stability after tap switching. Typically, the function can be determined by experimental data fitting, historical operation data analysis, or based on a physical model of the power system, thereby accurately describing how the operation at the previous time point affects the power loss and system state at the current time point. This transfer function is used to describe the change in system power loss after selecting different tap switching schemes at each time step.

[0128] In dynamic programming, the construction stage cost function C(t+k,u) is used to represent the power loss cost when operation u is selected at time point t+k. The construction expression of the stage cost function C(t+k,u) is: C(t+k,u)=r(S(t+k,u),u), where r(S,u) is the functional relationship between power loss and operation, which represents the total power loss after selecting u;

[0129] The stage cost function is used to evaluate the immediate cost when selecting different operations at different time points. Combined with the state transfer function, the optimal strategy can be recursively solved.

[0130] Using the idea of ​​dynamic programming, the optimal value problem at each time point is recursively solved, and the optimal value function M(t+k) is defined as the minimum cumulative power loss after the time point t+k. The calculation expression is obtained by recursive calculation: M(t+k)=min u∈U {C(t+k,u)+M(t+k+1)}, where U represents the set of all existing operations;

[0131] This formula represents the minimum cumulative cost after selecting the optimal operation u at time point t+k. Through recursive calculation, the optimal power loss from the current time point to the future time point can be obtained.

[0132] In dynamic programming, it is very important to set boundary conditions. Boundary conditions are used to determine the starting point or end point of recursive calculation. Usually, the optimal value function M(t+k) at the last time point t+N is set as the known final value. Here, the optimal value function M(t+k) is defined as: M(t+k)=C(t+k, u * ), where u * is the operation selected at the last time point. The boundary conditions ensure that the recursive process can be terminated correctly and provide a basis for the inverse solution. N represents the last time step in the prediction time range.

[0133] Finally, through the reverse backtracking method, starting from the boundary conditions and step by step back, the optimal switching strategy at each time point is constructed. The optimal strategy Φ(t+k) is defined as the optimal operation selected at each time point. The specific expression is: Φ(t+k)=argmin u∈U {C(t+k,u)+M(t+k+1)}, the optimal strategy Φ(t+k) on the entire time series is obtained by back-calculation, and this strategy is applied in actual operation for tap switching to ensure that the power loss of the system is minimized at every moment.

[0134] According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions;

[0135] After the optimal tap change strategy is obtained through dynamic programming optimization, the specific process of real-time control of the on-load tap changer switching action is as follows:

[0136] First, according to the switching time point and corresponding operation determined in the optimal strategy, specific operation instructions are generated;

[0137] These instructions involve switching the taps to specified target positions to minimize power loss or optimize system performance.

[0138] Subsequently, the control system executes these instructions through actuators (such as motors or hydraulic drive systems) to ensure that the taps are switched at the specified time points;

[0139] The entire process requires real-time monitoring of the system's operating status to ensure the accuracy and timeliness of the switching action, and to adjust the instructions when necessary to cope with dynamic changes in the operating environment.

[0140] Adjusting instructions when necessary means monitoring the operating status of the converter transformer and the power system in real time during the execution of the optimal tap switching strategy. If unexpected changes in the system operating environment are detected, such as abnormal load fluctuations, sharp changes in voltage, or deviations of system parameters from the expectations of the prediction model, these may affect the effectiveness of the switching operation. In this case, the control system needs to re-evaluate the current switching strategy based on the latest real-time data and adjust the original operating instructions. For example, postpone or advance the switching time, or change the target position of the tap to ensure that the system can still maintain optimal performance and safety under the new operating conditions. This dynamic adjustment mechanism ensures that the system can flexibly respond to complex operating environments and avoid increased power losses or system instability due to external changes.

[0141] The present invention uses the above-mentioned converter transformer on-load tap changer control method to construct a time series model and utilize a dynamic programming optimization method to predict and reasonably arrange the switching timing in advance, reduce unnecessary operations, reduce mechanical wear, extend the service life of the equipment, and improve the long-term reliability of the system.

[0142] The present invention optimizes the switching strategy, introduces a quantitative index of power loss into the cost function, and uses dynamic programming to globally optimize the switching strategy, so as to screen out the switching scheme with the minimum power loss, so that each tap switching can be carried out with the minimum power loss, thereby improving the economy and energy efficiency of the system operation and enhancing the stability of the power system.

[0143] The present invention provides Figure 2 A converter transformer on-load tap changer control system shown includes a data acquisition and model building module, a state prediction module, an optimal switching timing determination module, a switching cost calculation module, a cost function construction and evaluation module, a dynamic programming optimization module, and a real-time control execution module;

[0144] Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status.

[0145] The constructed time series model is used to predict the changing trend of the operating status of the converter transformer in the future.

[0146] Determine the best time to switch the tap of the converter transformer according to the predicted trend of operation status change;

[0147] For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost;

[0148] Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss.

[0149] The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment.

[0150] According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions;

[0151] A converter transformer on-load tap changer control method provided in an embodiment of the present invention is implemented by the above-mentioned converter transformer on-load tap changer control system. The specific method and process of a converter transformer on-load tap changer control system are detailed in the embodiment of the above-mentioned converter transformer on-load tap changer control method, which will not be repeated here.

[0152] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0153] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. 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.

[0154] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0155] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only one. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0156] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0157] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0158] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0159] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0160] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A converter transformer on-load tap changer control method, characterized in that: The following steps are involved: Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status. The constructed time series model is used to predict the changing trend of the operating status of the converter transformer in the future. Determine the best time to switch the tap of the converter transformer according to the predicted trend of operation status change; For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost; Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss. The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment. According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions.

2. A converter transformer on-load tap changer control method according to claim 1, characterized in that: Based on the collected converter transformer operating parameter data, the specific steps of constructing the time series model of the converter transformer operating status are as follows: Select a high-precision sensor system suitable for monitoring key parameters of converter transformers; Build a data acquisition and transmission system to capture the dynamic changes of converter transformer operating status in real time; After the data is transmitted to the central control system, the data is monitored and pre-processed in real time; After the preprocessing is completed, a time series model is constructed based on the cleaned data. The time series model is used to describe the change pattern of key operating parameters of the converter transformer over time and capture the dynamic characteristics thereof.

3. A converter transformer on-load tap changer control method according to claim 1, characterized in that: The specific steps for determining the optimal time point for switching the converter transformer tap are as follows: Use the constructed time series model to make multi-step forward predictions of the operating status in the future. t represents the key operating parameter, and its predicted value for the next k steps is expressed as: In the formula, is the predicted value at time point t+k, g(·) is the prediction function based on the time series model, θ is the model parameter set, n is the length of the historical data window, and k is the index of the time step; Based on the predicted operating state value, the predicted state change rate at each time point is calculated to capture the moment of drastic change of the future operating state, and the predicted state change rate V is defined as t+k for: ， In the formula, p is the nonlinear expansion exponent, and λ is the time attenuation factor; Calculate the predicted state change acceleration A t+k , the predicted state change acceleration can capture more subtle dynamic change characteristics, and the calculation expression is: ， Where Δt is the time step, A t+k represents the predicted state change acceleration at time point t+k; Combine the predicted state change rate and predicted state change acceleration to construct the discriminant function Q of the key time point t+k , the expression of the discriminant function is: ， In the formula, It represents the maximum value of the product of the predicted state change rate and the predicted state change acceleration at all future time points t+j. j represents the time point index, which is used to traverse each future time point. β is the weight coefficient of the predicted state change acceleration. Function Q t+k The state change characteristics at each time point are standardized; Through the discriminant function Q t+k The maximum value of is used to determine the optimal switching time point. The calculation expression for the optimal switching time point is: Where, t * Indicates the optimal switching time point.

4. A converter transformer on-load tap changer control method according to claim 3, characterized in that: The power loss difference at each determined switching time point is defined as the switching cost. The specific steps are as follows: Before the switching time point is determined, the power loss P under the current tap position is obtained. pre , the power loss is calculated by real-time monitoring of the electrical parameters of the system operation, and the calculation expression is: In the formula, I t is the current at the current tap position, R pre is the resistance of the current tap position, V t is the voltage at the current tap position, cos(φ pre ) is the power factor of the current tap position; Predict the power loss R after switching to the new tap position post , after switching, the power loss after switching to the new tap position is calculated as: In the formula, R post and cos(φ post ) is the resistance and power factor corresponding to the new tap position after switching, I t+k and V t+k are the current and voltage corresponding to the new tap position after switching; After obtaining the power loss data before and after the switching, the difference between the two is calculated to quantify the impact of the switching operation. The power loss difference ΔP is expressed as: ΔP = P post -P pre ; Finally, the calculated power loss difference ΔP is defined as the switching cost.

5. A converter transformer on-load tap changer control method according to claim 4, characterized in that: Construct a cost function to evaluate the power loss at each switching time point. The specific steps are: Define the power loss function P for each switching time point t+k t+k , power loss function P t+k It represents the power loss of the converter transformer in the future time series. Considering the changes of current, voltage, resistance and power factor, the power loss function P t+k The expression is: In the formula, I t is the current at time t, R t is the resistance at time t, V t is the voltage at time t, cos(φ t ) is the power factor at time t; Calculate the power loss difference ΔP before and after the switching time point t+k t+k , this difference directly reflects the impact of the switching operation on the system energy efficiency, and the calculation expression is: ΔP t+k =P post，t+k -P pre，t+k , where P pre，t+k is the power loss before switching, P pre，t+k is the power loss after switching.

6. A converter transformer on-load tap changer control method according to claim 5, characterized in that: The power loss difference ΔP t+k Introducing the cost function C t+k , the power loss at each switching time point is evaluated, and the expression of the cost function is: ， Where, T t+k is the time weight factor, which is used to adjust the importance of the switching time point, and α is an exponential parameter that controls the degree of nonlinearity of the function; Using the defined cost function C t+k , perform cost evaluation on all switching time points t+k, specifically traversing each existing switching time point in the future time period and calculating the corresponding cost value; The cost values ​​generated at all switching time points are used to create a data set, and the cost values ​​in the data set are sorted in order, and the time point with the smallest cost value is selected from all switching time points as the optimal switching time.

7. A converter transformer on-load tap changer control method according to claim 6, characterized in that: The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. The specific steps are as follows: First, define the state transfer function S(t+k,u), where u represents the tap switching operation at time point t+k, S(t+k,u) describes the current state transferred to the next time point by selecting u, and the state transfer function is expressed as: S(t+k,u)=P t+k +f(S(t+k-1,u-1)), where P t+k is the power loss at time point t+k, and the function f(S(t+k-1,u-1)) represents the influence of the state at the previous time point on the current state; In dynamic programming, the stage cost function C(t+k,u) is constructed to represent the power loss cost when operation u is selected at time point t+k. The construction expression of the stage cost function C(t+k,u) is: C(t+k,u)=r(S(t+k,u),u), where r(S,u) is the functional relationship between power loss and operation, and represents the total power loss after selecting u.

8. A converter transformer on-load tap changer control method according to claim 7, characterized in that: Using the idea of ​​dynamic programming, the optimal value problem at each time point is recursively solved, and the optimal value function M(t+k) is defined as the minimum cumulative power loss after the time point t+k. The calculation expression is obtained by recursive calculation: M(t+k)=min u∈U {C(t+k,u)+M(t+k+1)}, where U represents the set of all existing operations; In dynamic programming, boundary conditions are used to determine the starting point or end point of the recursive calculation. The optimal value function M(t+k) at the last time point t+N is set as the known final value. Here, the optimal value function M(t+k) is defined as: M(t+k)=C(t+k, u * ), where u * is the operation selected at the last time point, and N represents the last time step in the prediction time range; Through the reverse backtracking method, we start from the boundary conditions and backtrack step by step to build the optimal switching strategy at each time point. The optimal strategy Φ(t+k) is defined as the optimal operation selected at each time point. The specific expression is: Φ(t+k)=argmin u∈U {C(t+k,u)+M(t+k+1)}, the optimal strategy Φ(t+k) on the entire time series is obtained by back-calculation, and this strategy is applied in actual operation for tap switching to ensure that the power loss of the system is minimized at every moment.

9. A converter transformer on-load tap changer control method according to claim 1, characterized in that: After the optimal tap switching strategy is obtained through dynamic programming optimization, the specific process of real-time control of the switching action of the on-load tap changer is as follows: First, according to the switching time point and corresponding operation determined in the optimal strategy, specific operation instructions are generated; The control system then executes these instructions through the actuators to ensure that the taps are switched at the specified time.

10. A converter transformer on-load tap changer control system, used to implement the converter transformer on-load tap changer control method according to any one of claims 1 to 9, characterized in that: It includes data acquisition and model building module, state prediction module, optimal switching timing determination module, switching cost calculation module, cost function construction and evaluation module, dynamic programming optimization module and real-time control execution module; Through high-precision sensors and data acquisition systems, the key operating parameters of the converter transformer at each moment are monitored in real time. Based on the collected operating parameter data, a time series model of the converter transformer operating status is constructed. The model describes the law of changes in operating parameters over time and captures the dynamic characteristics of the operating status. The constructed time series model is used to predict the changing trend of the operating status of the converter transformer in the future. Determine the best time to switch the tap of the converter transformer according to the predicted trend of operation status change; For each determined switching time point, the power loss difference before and after the tap switching is obtained and defined as the switching cost; Construct a cost function to evaluate the power loss at each switching time point. The cost function considers the minimization of power loss, takes the difference in power loss before and after switching as the optimization target, calculates the power loss at all switching time points, and selects the switching solution with the minimum power loss. The cost function is solved by using the dynamic programming optimization method to obtain the optimal tap switching strategy. By decomposing the power loss problem into multiple sub-problems, the switching strategy at each time point is gradually optimized to ensure that the power loss of the system is minimized at every moment. According to the optimal tap switching strategy obtained by dynamic programming optimization, the switching action of the on-load tap changer is controlled in real time, and the optimal strategy is converted into actual operation instructions.

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