Switching method and device of primary and secondary fusion switch, medium and program product

Abstract

The invention discloses a switching method and device of a primary and secondary fusion switch, a medium and a program product, and relates to the field of electric power intelligent dispatching, and the method comprises the steps: obtaining real-time electrical parameters and historical electrical parameters of an operation power supply; determining a system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters, and determining a system sampling period according to the system disturbance level; collecting a target electrical parameter of a power supply to be switched in a system sampling period, and calculating a switching evaluation index according to the real-time electrical parameter and the target electrical parameter; according to the switching evaluation index and the system disturbance level, determining a dynamic control parameter of the power supply to be switched in; when the adjustment rate of the dynamic control parameter is greater than a first preset threshold value and the switching evaluation index is smaller than a second preset threshold value, generating a switching enable signal; and controlling the primary and secondary fusion switch to execute switching operation according to the switching enable signal. According to the invention, the transient response performance in the power supply switching process can be improved.

Description

Technical Field

[0001] This application relates to the field of intelligent power dispatching, and particularly to a switching method, device, medium, and program product for a primary-secondary integrated switch. Background Art

[0002] With the intelligent development of the power system, higher requirements for power supply reliability have been put forward in key load places such as data centers and hospitals. These places are usually equipped with multiple power supply sources such as mains power, generators, and energy storage systems, and it is necessary to switch between different power supply sources to ensure power supply continuity. During the switching process, due to the differences in frequency and phase of different power sources, and the extremely high requirements of the load for power quality, optimizing the transient characteristics during the power source switching process has become an important technical issue.

[0003] The power source switching schemes in the related art usually adopt synchronous detection technology to achieve the switching of different power sources. This scheme first detects the phase difference between the power source to be switched in and the operating power source through a phase-locked loop circuit, and triggers the switching operation when the phase difference reaches the set range. During the switching process, the output parameters of the power source to be switched in are adjusted through a PID controller, and an LC filter network is used to suppress the voltage fluctuation during the switching process. At the same time, a buffer circuit is adopted to store the energy at the moment of switching, which is used to compensate for the power fluctuation during the switching process.

[0004] However, in practical applications, the linear characteristics of the PID controller result in a slow response speed under large disturbance conditions, and it is difficult to accurately track the rapid changes of the load. Summary of the Invention

[0005] This application provides a switching method, device, medium, and program product for a primary-secondary integrated switch, which is used to improve the transient response performance during the power source switching process.

[0006] In a first aspect, this application provides a switching method for a primary-secondary integrated switch, which is applied to a switch switching device. The method includes: obtaining the real-time electrical parameters and historical electrical parameters of the operating power source; determining the system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters, and determining the system sampling period according to the system disturbance level; the system sampling period is inversely proportional to the system disturbance level; collecting the target electrical parameters of the power source to be switched in within the system sampling period, and calculating a switching evaluation index according to the real-time electrical parameters and the target electrical parameters; the switching evaluation index includes a voltage amplitude deviation coefficient, a frequency stability coefficient, and a phase matching coefficient; determining the dynamic control parameters of the power source to be switched in according to the switching evaluation index and the system disturbance level; generating a switching enable signal when the adjustment rate of the dynamic control parameters is greater than a first preset threshold and the switching evaluation index is less than a second preset threshold; controlling the primary-secondary integrated switch to perform a switching operation according to the switching enable signal.

[0007] In the above embodiments, the switch switching device obtains the operating power parameters in real time and dynamically adjusts the system sampling period, and combines the switching evaluation index to perform switch control, so that the control strategy can be flexibly adjusted according to the system disturbance level during the switching process; at the same time, by shortening the sampling period when the disturbance is large, the response speed is increased, and when the disturbance is small, the sampling period is appropriately extended to reduce the system overhead.

[0008] Combined with some embodiments of the first aspect, in some embodiments, the steps of determining the system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters and determining the system sampling period according to the system disturbance level specifically include: obtaining multiple groups of historical electrical parameter samples within a preset time window; performing a moving average filter on the multiple groups of historical electrical parameter samples to obtain the reference electrical parameters; calculating the voltage change rate, frequency change rate, and phase change rate of the real-time electrical parameters relative to the reference electrical parameters; comparing the voltage change rate, frequency change rate, and phase change rate with the corresponding disturbance level determination thresholds respectively to obtain the numerical comparison results; determining the highest disturbance level from a preset plurality of disturbance levels as the system disturbance level according to the numerical comparison results; the determination thresholds of the disturbance levels increase as the disturbance levels increase; determining the system sampling period according to the system disturbance level.

[0009] In the above embodiments, the switch switching device obtains the reference parameters by performing a moving average filter on the historical data, calculates the multi-dimensional change rates in combination with the real-time parameters, and uses the progressive disturbance level determination thresholds to achieve the precise division of the system disturbance degree, which can effectively suppress the influence of data noise and improve the accuracy of the disturbance level determination.

[0010] Combined with some embodiments of the first aspect, in some embodiments, the steps of collecting the target electrical parameters of the power supply to be switched in during the system sampling period and calculating the switching evaluation index according to the real-time electrical parameters and the target electrical parameters specifically include: collecting the target electrical parameters of the power supply to be switched in during the system sampling period; extracting the effective value of the operating voltage, operating frequency, and operating phase angle from the real-time electrical parameters, and extracting the target voltage effective value, target frequency, and target phase angle from the target electrical parameters; calculating the voltage amplitude deviation coefficient based on the effective value of the operating voltage and the target voltage effective value, calculating the frequency stability coefficient based on the operating frequency and the target frequency, and calculating the phase matching coefficient based on the operating phase angle and the target phase angle; determining the weight coefficients respectively matched with the voltage amplitude deviation coefficient, frequency stability coefficient, and phase matching coefficient, and calculating the switching evaluation index by weighted calculation.

[0011] In the above embodiments, the switch switching device extracts the characteristic parameters in three dimensions of voltage, frequency, and phase, and comprehensively evaluates the switching conditions by using the weighted calculation method. The flexible configuration of the weight coefficients enables the system to adjust the importance of each parameter according to the actual application scenario, improving the adaptability of the switching evaluation.

[0012] In combination with some embodiments of the first aspect, in some embodiments, before the step of determining the dynamic control parameters of the power supply to be switched in according to the switching evaluation index and the system disturbance level, the method further includes: selecting initial control parameters from a preset multiple sets of control parameter templates based on the system disturbance level; calculating the correction coefficients of each parameter in the initial control parameters according to the switching evaluation index; determining the dynamic control parameters of the power supply to be switched in according to the initial control parameters and the corresponding correction coefficients; the control parameters include a voltage regulation coefficient, a frequency regulation coefficient, and a phase regulation coefficient; there is an exponential function relationship between the correction coefficient and the switching evaluation index, and the correction coefficient exponentially decays as the switching evaluation index increases.

[0013] In the above embodiment, the switch switching device selects the initial control parameters based on the system disturbance level, and realizes the dynamic adjustment of the parameters through the correction coefficient. The exponential function relationship between the correction coefficient and the evaluation index ensures the smooth transition of the control parameters with the change of the state, and effectively avoids the system oscillation caused by parameter mutation.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the dynamic control parameters of the power supply to be switched in according to the initial control parameters and the corresponding correction coefficients specifically includes: using the system disturbance level, the switching evaluation index, and the historical switching data including overshoot, regulation time, and steady-state error as training samples, and training a correction coefficient model by using the polynomial regression method; the order of the regression polynomial of the polynomial regression method does not exceed three; based on the correction coefficient model, determining the reference value matrix of the correction coefficients; the reference value matrix includes a voltage correction coefficient, a frequency correction coefficient, and a phase correction coefficient; according to the reference value matrix, calculating the statistical distribution characteristics of each correction coefficient under different disturbance levels, and constructing a piecewise linear regression model based on the statistical distribution characteristics; the statistical distribution characteristics include mean, variance, and skewness; inputting the system disturbance level and the switching evaluation index into the piecewise linear regression model to obtain the real-time correction coefficient; calculating the dynamic control parameters of the power supply to be switched in according to the real-time correction coefficient and the initial control parameters.

[0015] In the above embodiment, the switch switching device trains the correction coefficient model by using polynomial regression and constructs a dynamic parameter adjustment mechanism in combination with piecewise linear regression.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of controlling the primary-secondary integrated switch to perform a switching operation according to the switching enable signal, the method further includes: real-time monitoring the transient response waveform of the primary-secondary integrated switch during the switching process; extracting the characteristic parameters of the transient response waveform; the characteristic parameters include overshoot, regulation time, and steady-state error; when the characteristic parameters exceed the preset performance index range, adjusting the dynamic control parameters.

[0017] In the above embodiments, the switch switching device monitors the transient response characteristics during the switching process in real time, and adjusts the control parameters in a timely manner when the performance indicators exceed the limits, ensuring that the system can continuously optimize the control effect during actual operation and improving the robustness of the system.

[0018] Combined with some embodiments of the first aspect, in some embodiments, when the characteristic parameters exceed the preset performance index range, the steps of adjusting the dynamic control parameters specifically include: calculating the deviation values of the overshoot, adjustment time, and steady-state error of the transient response waveform respectively from the corresponding performance indicators; determining the initial adjustment directions of the voltage adjustment coefficient, frequency adjustment coefficient, and phase adjustment coefficient according to the positive and negative signs of each deviation value; iteratively adjusting the dynamic control parameters according to a preset step size, and recording the new transient response characteristics after each adjustment; if the adjusted characteristic parameters are better than those before adjustment, keep the current adjustment direction unchanged and increase the step size by a preset increase coefficient; if the adjusted characteristic parameters are worse than those before adjustment, reverse the adjustment direction and decrease the step size by a preset decrease coefficient; count the adjustment effects of a preset number, and record the corresponding adjusted dynamic control parameters when the adjustment direction changes continuously or the step size is less than the minimum threshold.

[0019] In the above embodiments, the switch switching device adopts an iterative optimization strategy based on the performance index deviation, and realizes the precise optimization of the control parameters by dynamically adjusting the step size and direction, which can avoid the oscillation during the parameter adjustment while ensuring the convergence efficiency, and realizes the stable optimization of the control parameters.

[0020] In a second aspect, an embodiment of the present application provides a switch switching device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the switch switching device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product containing instructions, when the computer program product runs on the switch switching device, enabling the switch switching device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, including instructions, when the instructions run on the switch switching device, enabling the switch switching device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] Understandably, the switching device provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be elaborated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of a dynamic sampling mechanism based on the system disturbance level and a multi-dimensional switching evaluation system, the disturbance level is determined by real-time calculating the change rate of electrical parameters, and the sampling period is dynamically adjusted accordingly, so that the system can maintain an appropriate response speed under different disturbance intensities. The comprehensive evaluation of three dimensions of voltage, frequency, and phase ensures the comprehensiveness of the switching conditions, and the real-time adjustment of dynamic control parameters improves the system adaptability. Therefore, the response speed can be improved while ensuring the switching stability. It effectively solves the problems of response lag or resource waste caused by a fixed sampling period in the prior art, and realizes the efficient and stable control of the power supply switching process.

[0025] 2. Due to the adoption of a parameter template selection mechanism based on the disturbance level and a correction coefficient adjustment method with exponential decay, the initial control parameters are selected from the preset templates to establish a reference control strategy, and the correction coefficients of each parameter are calculated according to the switching evaluation index for dynamic adjustment, so that the control parameters can change smoothly with the system state. It effectively solves the problems of system oscillation caused by fixed or severely adjusted control parameters in the prior art, as well as the poor convergence in the parameter optimization process, realizes the adaptive optimization of control parameters, and improves the dynamic control performance of the system.

[0026] 3. Due to the adoption of real-time transient response monitoring and a parameter adjustment mechanism based on performance indicators, by monitoring characteristic parameters such as overshoot, regulation time, and steady-state error during the switching process, and adjusting the control parameters in a timely manner when the indicators exceed the limit, the system can continuously optimize the control effect. The closed-loop feedback parameter adjustment strategy ensures the real-time correction of the control effect, so it can adapt to changes in various operating conditions. It effectively solves the problems of control effect decline caused by the lack of a real-time optimization mechanism in the prior art, as well as the unstable long-term operation performance of the system, and enhances the adaptability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flowchart of a switching method for a primary-secondary integrated switch in an embodiment of the present application; Figure 2 is another flowchart of a switching method for a primary-secondary integrated switch in an embodiment of the present application; Figure 3It is a schematic structural diagram of an entity device of the switch switching device in the embodiment of the present application. Specific embodiments

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular forms "a", "an", "the above", "the", and "this" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0030] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0031] In the power supply system of a large data center, due to continuous business expansion, multiple backup power supplies such as commercial power, diesel generators, and UPS power supplies have been deployed. During the operation of the system, power grid fluctuations often occur: sometimes it is a slight voltage fluctuation caused by the maintenance of the power supply bureau, sometimes it is a frequency jitter caused by the start and stop of large loads, and in severe cases, it may be a phase mutation caused by lightning strikes. The existing fixed-parameter switching scheme performs poorly in the face of such a complex and changeable power supply environment: it is too sensitive during minor disturbances, resulting in frequent mis-switching and affecting system stability; during severe disturbances, the response is slow and it cannot switch to the backup power supply in time.

[0032] In the related art, a fixed-parameter switching scheme using phase-locked loop detection and PID control can be adopted to achieve power supply switching control. Specifically, a phase-locked loop circuit is used to detect the phase difference between the power supply to be switched in and the operating power supply, and when the phase difference is less than the set threshold, the switching is triggered. At the same time, the output parameters are adjusted by a PID controller to suppress the voltage fluctuation during the switching process. The scenario of the switching method of the primary-secondary integrated switch in the related art is introduced below.

[0033] An industrial park has adopted a common automatic switching device controlled by PLC on the market. This device uses a phase-locked loop circuit to detect the phase and adjusts the output parameters through a PID controller. Its switching logic is: when it detects that the main power supply voltage drops below 85% of the rated value and lasts for 100 ms, the switching process is triggered. However, in actual operation, due to the frequent start and stop of large motors in the park, the degree of power grid disturbance changes violently. Fixed judgment thresholds and PID parameters cannot adapt: when set conservatively, the response is too slow in the case of sudden voltage drops, resulting in sensitive equipment tripping; when set more aggressively, it will cause frequent misoperations due to slight power grid fluctuations, increasing the wear and tear of the switch life. At the same time, due to the linear characteristics of the PID controller, the adjustment process is slow under large disturbance conditions, and the voltage fluctuation amplitude during the switching process often exceeds 20%, causing protective shutdown of the load equipment.

[0034] By using the switching method of the primary-secondary integrated switch in the embodiment of the present application, the system disturbance level is determined by calculating the change rate of electrical parameters in real time, and the sampling period and control parameter template are dynamically selected based on the disturbance level, improving the timeliness and accuracy of switching. The following introduces the scenario where the switching method of the primary-secondary integrated switch in the present application is used.

[0035] A semiconductor manufacturing plant has adopted the dynamic adaptive switching scheme of the present application. This scheme dynamically divides the system disturbance into three levels: slight, medium, and severe by calculating the change rates of voltage, frequency, and phase in real time. When a short-circuit fault occurs in the power supply line is detected, the system immediately determines it as a severe disturbance, the sampling period is automatically shortened to 100 μs, and at the same time, a preset fast switching parameter template is enabled. On this basis, the control parameters are adjusted in real time according to the switching evaluation index to make the switching process smooth and controllable. The transient fluctuation during the switching process is controlled within 5%, and the entire process takes less than 20 ms, which is much lower than the sensitive time of the equipment.

[0036] It can be seen that by using the switching method of the primary-secondary integrated switch in the embodiment of the present application, while realizing the power supply switching function, it can also effectively solve the problem that the fixed parameter scheme cannot adapt to the complex power supply environment, and through multi-dimensional evaluation and adaptive control, the intelligence and precision of switching control are realized.

[0037] For easy understanding, the method provided in this embodiment is described in the following process in combination with the above scenario. Please refer to Figure 1 , which is a schematic flow diagram of the switching method of the primary-secondary integrated switch in the embodiment of the present application.

[0038] S101. Obtain the real-time electrical parameters and historical electrical parameters of the operating power supply.

[0039] Among them, the operating power supply refers to the power supply that is currently supplying power to the load and is used to provide continuous and stable power supply to the load; the real-time electrical parameters refer to the electrical characteristic data such as voltage, current, frequency, and phase of the operating power supply at the current moment and are used to reflect the real-time operating state of the power supply; the historical electrical parameters represent the sequence of electrical characteristic data of the operating power supply recorded over a period of time in history and are used as a reference benchmark for evaluating the stability of the power supply.

[0040] When the switch switching device needs to perform power switching, it is first necessary to evaluate the working state of the current operating power supply. Specifically, the switch switching device collects real-time electrical parameters such as the effective value of the voltage, frequency, and phase angle of the operating power supply through a sampling circuit, and at the same time reads the historical electrical parameters within a preset time window (such as the most recent 5 minutes) from the data storage unit. The sampling frequency of the sampling circuit is usually not less than 10 kHz to ensure that rapid changes in electrical parameters can be accurately captured.

[0041] In some embodiments, the acquisition and processing of electrical parameters can be achieved in various ways: Optionally, the switch switching device can use high-precision voltage transformers and current transformers to collect raw signals, amplify and filter them through a signal conditioning circuit, then convert the analog signals into digital quantities through a 16-bit or 24-bit analog-to-digital converter, and finally use a DSP for digital signal processing to obtain the required parameters; Optionally, the switch switching device can also directly use a digital watt-hour meter chip for sampling and read the processed electrical parameter data through an SPI or I2C interface. It can be understood that other types of sensors and signal processing methods can also be used to achieve the acquisition of electrical parameters, which are not limited here.

[0042] S102. Determine the system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters, and determine the system sampling period according to the system disturbance level.

[0043] Among them, the change rate refers to the ratio of the change amplitude of the real-time electrical parameters relative to the historical electrical parameters to time and is used to characterize the dynamic change characteristics of the electrical parameters; the system disturbance level represents the severity of the external interference received by the power system and is usually divided into multiple levels such as slight disturbance, medium disturbance, and severe disturbance; the system sampling period refers to the time interval for the switch switching device to collect the parameters of the power supply to be switched in and is used to balance the sampling accuracy and system overhead; the system sampling period is inversely proportional to the system disturbance level.

[0044] After obtaining the electrical parameters, the switch switching device needs to evaluate the disturbance state of the system to determine an appropriate sampling strategy. Specifically, first calculate the change rates of the real-time voltage, frequency, and phase relative to their historical averages, compare these change rates with preset multi-level disturbance thresholds, and select the highest disturbance level as the system disturbance level. Subsequently, dynamically adjust the sampling period according to the disturbance level. The higher the disturbance level, the shorter the sampling period, so as to improve the system's response speed to disturbances.

[0045] In some embodiments, the determination of the disturbance level and the determination of the sampling period can be achieved in various ways: Optionally, the switch switching device uses a moving average algorithm to filter the historical data to obtain a reference value, calculates the change rate by dividing the difference between the real-time value and the reference value by the time interval, compares the change rate with the grading thresholds {0.1, 0.3, 0.5, 0.7, 0.9} to determine the disturbance level, and then calculates the sampling period through the mapping function T = Tbase / (1 + k * level), where Tbase is the reference sampling period and k is the adjustment coefficient; Optionally, the switch switching device can also use wavelet transform to detect the signal mutation characteristics and determine the disturbance level according to the amplitude of the wavelet coefficients. It can be understood that other mathematical models and algorithms can also be used to evaluate the disturbance level, which is not limited here.

[0046] S103. Collect the target electrical parameters of the power supply to be switched in during the system sampling period, and calculate the switching evaluation index according to the real-time electrical parameters and the target electrical parameters.

[0047] Among them, the target electrical parameters represent the characteristic parameters such as the voltage, frequency, and phase of the power supply to be switched in, and are used to evaluate its matching degree with the operating power supply; the switching evaluation index includes the voltage amplitude deviation coefficient, the frequency stability coefficient, and the phase matching coefficient; the voltage amplitude deviation coefficient refers to the relative deviation between the target voltage and the operating voltage, and is used to measure the voltage matching degree; the frequency stability coefficient represents the following ability of the target frequency to the operating frequency and reflects the frequency synchronization; the phase matching coefficient is used to characterize the phase angle difference between the two power supplies and reflects the phase synchronization degree.

[0048] After determining the sampling period, the switch switching device needs to collect and evaluate the parameters of the power supply to be switched in. Specifically, the switch switching device continuously samples the power supply to be switched in according to the system sampling period to obtain parameters such as its effective voltage value, frequency, and phase angle. Then calculate the voltage amplitude deviation coefficient kv = |V2 - V1| / V1, the frequency stability coefficient kf = |f2 - f1| / f1, and the phase matching coefficient kp = |φ2 - φ1| / π respectively, and perform weighted summation according to the preset weight coefficient to obtain a comprehensive switching evaluation index.

[0049] In some embodiments, the calculation of the switching evaluation index can be achieved in various ways: Optionally, the switch switching device can adopt an adaptive weight algorithm to dynamically adjust the weights of various coefficients according to the current working conditions, and determine the final evaluation index through fuzzy inference. The weight coefficients are automatically adjusted according to the system disturbance level and load characteristics; Optionally, the switch switching device can also adopt a machine learning model based on historical switching data to establish a mapping relationship between parameter features and switching success rate through a neural network, and output the switching evaluation index. It can be understood that other evaluation methods can also be used to determine the satisfaction degree of the switching conditions, which is not limited here.

[0050] S104. Determine the dynamic control parameters of the power supply to be switched in according to the switching evaluation index and the system disturbance level.

[0051] Among them, the dynamic control parameter refers to the control quantity used to adjust the output characteristics of the power supply to be switched in, including voltage regulation coefficient, frequency regulation coefficient and phase regulation coefficient, which are used to realize the dynamic matching of power supply characteristics; the dynamic characteristic of the control parameter represents its ability to adaptively adjust with the change of the system state.

[0052] The switch switching device needs to determine an appropriate control strategy according to the current system state. Specifically, first select the reference control parameters matching the current disturbance level from the preset parameter template library, and then calculate the correction coefficient according to the switching evaluation index to dynamically adjust the reference parameters. The correction coefficient shows an exponential decay relationship with the switching evaluation index, ensuring that the control parameters can smoothly transition and avoiding system oscillations caused by mutations.

[0053] In some embodiments, the dynamic adjustment of the control parameters can be achieved in various ways: Optionally, the switch switching device adopts a model predictive control algorithm to establish a system state equation and solve the optimal control sequence online, and dynamically update the control parameters according to the prediction model. The adjustment of the control parameters is based on system constraints and performance indicators; Optionally, the switch switching device can also adopt an iterative learning control strategy to continuously optimize the control parameters by using the experience accumulated in previous switching processes. It can be understood that other control algorithms can also be used to realize the dynamic optimization of parameters, which is not limited here.

[0054] S105. Generate a switching enable signal when the adjustment rate of the dynamic control parameter is greater than the first preset threshold and the switching evaluation index is less than the second preset threshold.

[0055] Among them, the adjustment rate represents the change speed of the dynamic control parameter and is used to measure the response ability of the control system; the first preset threshold is the minimum requirement for the adjustment rate of the control parameter to ensure that the system has sufficient adjustment ability; the second preset threshold is the upper limit constraint of the switching evaluation index to ensure the full satisfaction of the switching conditions; the switching enable signal is a control command to trigger the switch action.

[0056] When the control parameters are adjusted in place and the switching conditions are met, the switch switching device needs to generate a switching control signal. Specifically, the time derivative of the control parameter is calculated in real time to obtain the adjustment rate, and the adjustment rate is compared with the first preset threshold to confirm that the control system has reached a stable state. At the same time, it is checked whether the switching evaluation index is lower than the second preset threshold to ensure switching safety. When both conditions are met, a switching enable signal is generated.

[0057] In some embodiments, the determination of the switching conditions can be achieved in various ways: Optionally, the switch switching device calculates the average change rate of the control parameter using a sliding time window, and comprehensively evaluates the switching conditions in combination with fuzzy decision rules, and triggers a switching signal when multiple safety constraints are met; Optionally, the switch switching device can also implement switching logic control using a state machine, and ensure the reliability of the switching process through multi-state conversion. It can be understood that other decision-making methods can also be used to determine the switching timing, which is not limited here.

[0058] S106. Control the primary-secondary integrated switch to perform a switching operation according to the switching enable signal.

[0059] Among them, the primary-secondary integrated switch is an intelligent switch device integrating primary switch equipment and secondary measurement and control units, which can realize functions such as power supply switching and status monitoring; the switching operation includes the complete process of disconnecting the operating power supply and connecting the power supply to be switched in, and it is necessary to ensure the continuity and safety of the switching process.

[0060] After receiving the enable signal, the switch switching device needs to perform an actual switch switching action. Specifically, first check the mechanical and electrical states of the switch body, and after confirming that the switching conditions are met, perform disconnection and closing operations according to the preset timing control strategy. During the switching process, the switch state and electrical parameters are monitored in real time to ensure the safety and reliability of the switching process.

[0061] In some embodiments, the switch switching control can be achieved in various ways: Optionally, the switch switching device adopts a control strategy based on a timing diagram to accurately control the action timing of each actuator, and ensures the reliability of the switching process through hardware interlock and software interlock, and records various status quantities during the switching process in real time; Optionally, the switch switching device can also adopt a distributed control architecture, decompose the switching control task into multiple sub-modules to cooperate to complete, and improve the reliability and flexibility of the system. It can be understood that other control methods can also be used to implement the switch switching operation, which is not limited here.

[0062] In the above embodiments, a parameter optimization scheme based on the disturbance level and the switching evaluation index is mainly introduced. In practical applications, technologies such as artificial intelligence algorithms and big data analysis can also be combined to further improve the prediction ability and optimization effect of the system. The scenarios of this embodiment are supplemented below.

[0063] A certain intelligent power grid demonstration area further optimized the application of this solution. They connected the switching device to the regional energy management system and established a self-learning model based on historical data. The system can analyze information such as weather data and load curves in advance to predict possible power grid disturbances and actively adjust the switching strategy. For example, when detecting that a thunderstorm is approaching, the system will automatically lower the disturbance determination threshold and increase the sampling frequency to prepare for possible power grid fluctuations. At the same time, by analyzing the transient response characteristics of each switch, the system continuously optimizes and corrects the coefficient model, making the switching process more and more accurate. Data after one year shows that the average switching time of the system has been shortened by 40%, the transient fluctuations have been reduced by 60%, and the power supply reliability has been improved to over 99.8%.

[0064] After combining the above scenarios, the following is a more specific process description of the method provided in this implementation. Please refer to Figure 2 , which is another process schematic diagram of the switching method of the primary-secondary integrated switch in the embodiment of this application.

[0065] S201. Obtain the real-time electrical parameters and historical electrical parameters of the operating power supply.

[0066] Referring to step S101, the switch switching device will obtain the real-time electrical parameters and historical electrical parameters.

[0067] S202. Determine the system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters, and determine the system sampling period according to the system disturbance level.

[0068] Referring to step S102, the switch switching device will determine the system disturbance level and the system sampling period.

[0069] In some embodiments, the switch switching device will obtain multiple groups of historical electrical parameter samples within a preset time window; perform moving average filtering on the multiple groups of historical electrical parameter samples to obtain the reference electrical parameters; calculate the voltage change rate, frequency change rate, and phase change rate of the real-time electrical parameters relative to the reference electrical parameters; compare the voltage change rate, frequency change rate, and phase change rate with the corresponding disturbance level determination thresholds respectively to obtain the numerical comparison results; determine the highest disturbance level from the preset multiple disturbance levels as the system disturbance level; the determination threshold of the disturbance level increases with the increase of the disturbance level; determine the system sampling period according to the system disturbance level.

[0070] Among them, the preset time window represents the time range for historical data collection, which is used to determine the reference interval for parameter analysis; the reference electrical parameter refers to the reference standard value obtained through data processing, which is used to evaluate the degree of change of real-time parameters; the change rate represents the dynamic change speed of electrical parameters, including three dimensions: voltage, frequency, and phase; the disturbance level determination threshold refers to the boundary value used to divide different disturbance degrees, which increases as the disturbance level increases; the system sampling period represents the time interval for subsequent parameter collection.

[0071] The switch switching device needs to evaluate the system disturbance state based on historical data and real-time data. Specifically, the switch switching device first collects multiple groups of historical electrical parameter samples within the preset time window, eliminates random fluctuations through moving average filtering, and obtains stable reference electrical parameters. Then, it calculates the voltage change rate, frequency change rate, and phase change rate of the real-time electrical parameters relative to the reference electrical parameters. Compare these three change rates with the determination thresholds of the corresponding levels respectively, and select the highest disturbance level as the current state of the system. Finally, according to the determined disturbance level, select the matching sampling time interval from the preset sampling period configuration table.

[0072] It should be noted that when calculating the change rates in the three dimensions of voltage, frequency, and phase, a weighted comprehensive evaluation mechanism should be adopted. First, normalize the change rate of each dimension and map it to the interval [0, 1]. Then, set the weight coefficients according to the sensitivity of the load to each parameter. The weight of the voltage change rate is taken as 0.4, the weight of the frequency change rate is taken as 0.35, and the weight of the phase change rate is taken as 0.25. When the change rates of multiple parameters are simultaneously close to the determination thresholds of different levels, the weighted summation method is used to obtain the comprehensive disturbance index. The disturbance level determination thresholds are divided according to {0.2, 0.4, 0.6, 0.8}, corresponding to four disturbance levels: slight, relatively light, medium, and severe. The length of the time window is determined according to the system response characteristics. For a conventional distribution system, it is 5 minutes, and for special loads sensitive to disturbances, it can be shortened to 1 minute. The selection of the window length needs to ensure that it can completely cover the rise and recovery stages of a disturbance process.

[0073] In some embodiments, the disturbance state evaluation can be achieved in various ways: Optionally, the switch switching device adopts the fuzzy comprehensive evaluation method, takes the three change rates of voltage, frequency, and phase as fuzzy variable inputs, defines the membership functions of different disturbance levels by establishing a fuzzy rule base, determines the system disturbance level using the maximum membership degree principle, and then looks up the appropriate sampling period according to the disturbance level; Optionally, the switch switching device can also adopt the evaluation method based on statistical features, calculates statistics such as the mean and variance of historical data to establish a normal distribution model, converts the deviation degree of real-time parameters into probability values, determines the disturbance level by setting a confidence interval, and selects a sampling strategy accordingly. It can be understood that other evaluation methods can also be used to judge the system disturbance state, which is not limited here.

[0074] S203. Collect the target electrical parameters of the power supply to be switched in during the system sampling period, and calculate the switching evaluation index based on the real-time electrical parameters and the target electrical parameters.

[0075] Referring to step S103, the switch switching device calculates the switching evaluation index.

[0076] In some embodiments, the switch switching device collects the target electrical parameters of the power supply to be switched in during the system sampling period; extracts the effective value of the operating voltage, operating frequency, and operating phase angle in the real-time electrical parameters, and extracts the target voltage effective value, target frequency, and target phase angle in the target electrical parameters; calculates the voltage amplitude deviation coefficient based on the effective value of the operating voltage and the target voltage effective value, calculates the frequency stability coefficient based on the operating frequency and the target frequency, and calculates the phase matching coefficient based on the operating phase angle and the target phase angle; determines the weight coefficients respectively matched by the voltage amplitude deviation coefficient, frequency stability coefficient, and phase matching coefficient, and calculates the switching evaluation index by weighted calculation.

[0077] Among them, the target electrical parameters represent the parameter values of the power supply to be switched in, and are used to establish the target reference for switching control; the amplitude deviation coefficient represents the quantization index of voltage matching degree and reflects the difficulty of voltage control; the frequency stability coefficient is the normalized representation of frequency difference and is used to evaluate the possibility of frequency synchronization; the phase matching coefficient represents the quantization value of phase angle deviation and reflects the selection basis at the switching moment; the weight coefficient refers to the importance of each parameter in the comprehensive evaluation.

[0078] After determining the sampling period, the switch switching device needs to evaluate the appropriateness of the switching conditions. Specifically, the switch switching device first acquires the voltage, frequency, and phase parameters of the power supply to be switched in with high precision within the sampling period, and at the same time obtains the real-time parameter values of the operating power supply. Then, the voltage amplitude deviation coefficient, frequency stability coefficient, and phase matching coefficient are calculated respectively. These coefficients are all normalized to ensure that the calculation results are within the range of [0, 1]. Finally, according to the characteristics of the current working condition, the weight values of each coefficient are determined, and a comprehensive switching evaluation index is obtained through weighted summation.

[0079] It should be noted that the weight coefficient of the switching evaluation index adopts an adaptive dynamic adjustment mechanism and is calculated in real time based on the load characteristics and system operating status. The weight calculation is based on three factors: the severity of the parameter deviation, the sensitivity of the load to each parameter, and the correlation between each parameter and the switching success rate in the historical switching data. Specifically in the calculation, each parameter is first standardized to a relative deviation value, and the min-max normalization method is used to map the value to the range of [0, 1]. Then, the deviation value is converted into a score through the exponential function e^(-k*x), where k is the sensitivity coefficient determined by the load characteristics. The weight coefficient of each parameter is determined by the product of the normalized score value and the historical correlation coefficient. The effective value range of the final switching evaluation index is [0, 1]. The smaller the value, the more ideal the switching condition. It is recommended to use 0.3 as the switching allowable threshold.

[0080] In some embodiments, the calculation of the switching evaluation index can be implemented in multiple ways: Optionally, the switch switching device adopts an adaptive weight method, dynamically adjusts the weight coefficients of each parameter according to the real-time state of the system, and determines the importance of the parameters by introducing a fuzzy evaluation matrix to achieve accurate evaluation of the switching conditions; Optionally, the switch switching device can also adopt a neural network evaluation method, use the voltage, frequency, and phase parameters as network inputs, and output a reasonable evaluation index through training to learn the optimal weight configuration. It can be understood that other evaluation methods can also be used to achieve the comprehensive evaluation of the switching conditions, which are not limited here.

[0081] S204. Select initial control parameters from a preset multiple sets of control parameter templates based on the system disturbance level.

[0082] Among them, the control parameter template represents a set of parameter schemes pre-configured for different disturbance levels and is used to provide a reference control strategy; the initial control parameter refers to the reference adjustment parameters selected from the template, including the voltage adjustment coefficient, frequency adjustment coefficient, and phase adjustment coefficient, and is used to establish an initial control reference; the parameter template library is a multiple sets of parameter configuration schemes stored by grading according to the disturbance level, and each set of schemes contains a complete set of control parameters.

[0083] After determining the system disturbance level, the switch switching device needs to establish an initial control strategy matching the current working condition. Specifically, the switch switching device first accesses the parameter template library and extracts the parameter configuration scheme corresponding to the current disturbance level. Then, according to the specific value of the disturbance level, interpolation calculation is used to obtain more accurate initial control parameters. The configuration scheme of the parameter template is adjusted as the disturbance level increases, and a higher disturbance level corresponds to more aggressive control parameters to improve the system response speed.

[0084] In some embodiments, the selection of the initial control parameters can be achieved in various ways: Optionally, the switch switching device uses the fuzzy rule inference method, takes the disturbance level as the input variable, defines the mapping relationship between the disturbance level and the parameter template by establishing a fuzzy rule base, and uses the centroid method to defuzzify to obtain the optimal initial parameter set; Optionally, the switch switching device can also adopt a parameter optimization strategy based on historical data, statistically analyze the parameter distribution characteristics of successful switching cases under different disturbance levels, and select the parameter set with the best switching effect as the initial parameter. It can be understood that other parameter selection methods can also be used to determine the initial control parameters, which are not limited here.

[0085] S205. Calculate the correction coefficient of each parameter in the initial control parameters according to the switching evaluation index.

[0086] Among them, the correction coefficient represents the adjustment ratio factor for the initial control parameters, which is used to realize the dynamic optimization of the parameters; parameter correction refers to the process of adjusting the initial parameters based on the switching evaluation index, which is used to improve the matching degree of the control parameters with the actual working condition; the adjustment direction represents the increasing and decreasing trend of the correction coefficient, which reflects the tendency of parameter optimization.

[0087] After obtaining the initial control parameters, the switch switching device needs to correct the parameters according to the actual switching conditions. Specifically, the switch switching device first analyzes the deviation characteristics of the three components of voltage, frequency, and phase in the switching evaluation index and establishes a correction model for each parameter. Then, calculate the correction coefficient corresponding to each control parameter. The correction coefficient shows an exponential decay relationship with the switching evaluation index to ensure the smoothness and stability of parameter adjustment.

[0088] In some embodiments, the calculation of the correction coefficient can be achieved in various ways: Optionally, the switch switching device uses the adaptive weight algorithm, determines the calculation formula of the corresponding correction coefficient according to the weights of the components of the switching evaluation index, and dynamically adjusts the correction strength through parameter sensitivity analysis to achieve accurate correction of the control parameters; Optionally, the switch switching device can also adopt the model prediction method, establish a mathematical model of the switching process, and obtain the correction coefficient that optimizes the performance index through online optimization calculation. It can be understood that other calculation methods can also be used to determine the correction coefficient, which are not limited here.

[0089] S206. Determine the dynamic control parameters of the power supply to be connected according to the initial control parameters and the corresponding correction factors.

[0090] Among them, the dynamic control parameter refers to the control quantity actually applied after correction, which is used to adjust the output characteristics of the power supply to be connected; parameter setting represents the process of combining the initial control parameters with the correction factors to generate the final control strategy; parameter constraint refers to the range limit of the control parameter values to ensure the rationality of parameter adjustment.

[0091] After obtaining the correction factors, the switch switching device needs to determine the dynamic control parameters actually applied. Specifically, the switch switching device multiplies the initial control parameters by the corresponding correction factors to obtain the preliminary dynamic control parameter values. Then, amplitude limiting processing is performed according to the preset parameter constraint conditions to ensure that all parameters are within a reasonable range. Finally, the parameters are smoothed to avoid system instability caused by parameter mutations.

[0092] In some embodiments, the determination of the dynamic control parameters can be achieved in multiple ways: Optionally, the switch switching device adopts a parameter optimization algorithm, takes the corrected parameters as the optimization objective, and based on multiple constraint conditions, obtains the optimal control parameters that meet all constraints through iterative calculation; Optionally, the switch switching device can also adopt a fuzzy control strategy, establish fuzzy rules using expert experience, and determine the final dynamic control parameters through inference operations. It can be understood that other optimization methods can also be used to determine the dynamic control parameters, which are not limited here.

[0093] In some embodiments, the switch switching device uses the system disturbance level, the switching evaluation index, and the historical switching data including overshoot, adjustment time, and steady-state error as training samples, and uses the polynomial regression method to train and generate a correction factor model; the order of the regression polynomial of the polynomial regression method does not exceed three; based on the correction factor model, determine the reference value matrix of the correction factors; the reference value matrix includes the voltage correction factor, the frequency correction factor, and the phase correction factor; according to the reference value matrix, calculate the statistical distribution characteristics of each correction factor under different disturbance levels, and construct a piecewise linear regression model based on the statistical distribution characteristics; the statistical distribution characteristics include mean, variance, and skewness; input the system disturbance level and the switching evaluation index into the piecewise linear regression model to obtain the real-time correction factor; calculate the dynamic control parameters of the power supply to be connected according to the real-time correction factor and the initial control parameters.

[0094] Among them, the training samples refer to the historical data set used to establish the correction model, including the corresponding relationship between the system state and the switching effect; the correction coefficient model represents the mathematical description of parameter correction, used to predict the optimal correction value; the reference value matrix refers to the set of reference values of the correction coefficient under different conditions, used to establish the correction rule; the statistical distribution feature represents the numerical rule of the correction coefficient, reflecting the general trend of parameter correction.

[0095] After obtaining the switching evaluation index, the switch switching device needs to establish a scientific parameter correction mechanism. Specifically, the switch switching device first trains the correction coefficient model based on the historical switching data, and uses a polynomial regression method not exceeding the third order to fit the relationship between the system state and the correction effect. Then, the reference value matrix is calculated through the model, and the distribution characteristics of the correction coefficient under different disturbance levels are analyzed. Finally, a piecewise linear regression model is constructed to map the current system state to specific correction coefficients, realizing the dynamic adjustment of parameters.

[0096] It should be noted that the correction coefficient model is constructed by using the polynomial regression method. In the training stage, the system disturbance level and the switching evaluation index are used as input features, and the historical switching data including the overshoot, adjustment time, and steady-state error are used as training labels. The model parameters are optimized by minimizing the mean square error between the predicted value and the actual correction coefficient. The model order does not exceed the third order to avoid overfitting. When the model is used, the current system disturbance level and the switching evaluation index are input, and a reference value matrix including the voltage correction coefficient, frequency correction coefficient, and phase correction coefficient is output.

[0097] The piecewise linear regression model is constructed based on the output results of the correction coefficient model. During the training process, the statistical distribution characteristics (mean, variance, skewness) of each correction coefficient under different disturbance levels in the reference value matrix are used to determine the linear function parameters of each interval by minimizing the piecewise linear fitting error. The model adopts a piecewise structure design, which can better adapt to the parameter adjustment requirements under different disturbance levels. In actual applications, the model receives the system disturbance level and the switching evaluation index as inputs and outputs real-time correction coefficients for dynamically adjusting control parameters. The two models cooperate with each other to jointly realize the mapping from historical data to real-time parameter adjustment, ensuring the adaptive optimization ability of the switching process.

[0098] In some embodiments, the calculation of the correction coefficient can be implemented in multiple ways: Optionally, the switch switching device uses the support vector regression method to map the historical samples to a high-dimensional feature space and constructs a nonlinear regression model through a kernel function to achieve accurate prediction of the correction coefficient; Optionally, the switch switching device can also use the random forest algorithm to integrate the prediction results of multiple decision trees to improve the generalization ability and robustness of the correction model. It can be understood that other modeling methods can also be used to determine the correction coefficient, which is not limited here.

[0099] S207. Determine the dynamic control parameters of the power supply to be switched in according to the switching evaluation index and the system disturbance level.

[0100] Referring to step S104, the switch switching device determines the dynamic control parameters.

[0101] S208. Generate a switching enable signal when the adjustment rate of the dynamic control parameters is greater than a first preset threshold and the switching evaluation index is less than a second preset threshold.

[0102] Referring to step S105, the switch switching device generates a switching enable signal.

[0103] S209. Control the primary-secondary integrated switch to perform a switching operation according to the switching enable signal.

[0104] Referring to step S106, the switch switching device controls the switch to perform a switching operation.

[0105] S210. Real-time monitor the transient response waveform of the primary-secondary integrated switch during the switching process.

[0106] Among them, the transient response waveform represents the dynamic change curve of electrical parameters during the switch switching process, which is used to evaluate the switching effect; the monitoring point refers to the critical moment of waveform sampling, which is used to capture the characteristic changes; the sampling accuracy represents the time and amplitude resolution of waveform acquisition, which affects the accuracy of the monitoring result.

[0107] While performing the switching operation, the switch switching device needs to perform real-time monitoring on the switching process. Specifically, the switch switching device collects the instantaneous values of voltage and current during the switching process through a high-speed sampling circuit to form a continuous transient response waveform. The sampling frequency is not less than 10 kHz to ensure that the fast-changing transient characteristics can be accurately captured. At the same time, record the waveform characteristics of key time nodes to provide a basis for subsequent analysis.

[0108] In some embodiments, the transient response monitoring can be realized in various ways: Optionally, the switch switching device adopts digital oscilloscope technology, sets multiple trigger conditions and sampling channels, and records the complete switching process waveform through a caching mechanism to accurately capture the transient characteristics; Optionally, the switch switching device can also adopt a distributed measurement architecture, synchronously sample at multiple key points, and reconstruct the complete transient process through data fusion. It can be understood that other monitoring methods can also be used to record the transient response, which is not limited here.

[0109] S211. Extract the characteristic parameters of the transient response waveform.

[0110] Among them, the characteristic parameters include overshoot, settling time, and steady-state error.

[0111] Among them, the overshoot represents the maximum deviation of the waveform beyond the steady-state value, reflecting the impact degree of the switching process; the settling time refers to the time required for the waveform to reach stability from the start of switching, used to measure the rapidity of the switching process; the steady-state error represents the residual deviation when the system finally stabilizes, reflecting the switching accuracy; the characteristic parameters refer to the key indicators characterizing the transient response quality.

[0112] After obtaining the transient response waveform, the switch switching device needs to extract the characteristic parameters reflecting the switching performance. Specifically, the switch switching device first preprocesses the waveform data, including filtering, denoising, and reference correction. Then it calculates the maximum deviation value of the waveform to obtain the overshoot, counts the time required for the waveform to enter the stable interval to obtain the settling time, and calculates the difference between the final steady-state value and the target value to obtain the steady-state error.

[0113] In addition, the transient response waveform sampling adopts an adaptive sampling rate strategy. The basic sampling frequency is set to 20 kHz and automatically increased to 50 kHz when rapid changes are detected. The sampled data is denoised by wavelet transform, and the db4 wavelet basis function is selected for 3-layer decomposition to retain the effective signal while suppressing high-frequency noise. The feature extraction uses the sliding window method. The window length is 1 / 10 of the switching time, and the step size is 50 times the sampling period. For the data within each window, statistical features such as the mean, standard deviation, and peak factor are calculated, and transient characteristics such as overshoot and oscillation are identified through the time series changes of these features. At the same time, the Hilbert transform is used to calculate the instantaneous frequency and phase features to achieve a complete characterization of the dynamic characteristics of the switching process. To improve the reliability of feature extraction, median filtering is used to smooth the extraction results, and the filter window size is set to 5 sampling points.

[0114] In some embodiments, the extraction of characteristic parameters can be achieved in multiple ways: Optionally, the switch switching device uses the wavelet transform method to perform multi-scale decomposition on the waveform, extracts characteristic parameters from different frequency bands, and obtains accurate performance indicators through reconstruction; Optionally, the switch switching device can also use pattern recognition technology to establish a waveform feature template library, and identify key feature points and calculate performance parameters through a matching algorithm. It can be understood that other signal processing methods can also be used to extract characteristic parameters, which are not limited here.

[0115] S212. When the characteristic parameters exceed the preset performance index range, adjust the dynamic control parameters.

[0116] Among them, the preset performance index is the performance requirement that the switching process needs to meet, including the maximum allowable overshoot, the longest settling time, and the maximum steady-state error; the parameter adjustment refers to the process of optimizing the control parameters according to the performance deviation; the adjustment strategy represents the specific methods and steps of parameter optimization.

[0117] After obtaining the characteristic parameters, the switch switching device needs to evaluate the switching performance and perform necessary optimizations. Specifically, the switch switching device compares the extracted characteristic parameters with the preset performance indicators. When any parameter exceeds the allowable range, it analyzes the degree and direction of the excess. Then, according to the preset adjustment rules, it pertinently modifies the dynamic control parameters to gradually improve the switching performance.

[0118] In some embodiments, parameter adjustment can be achieved in various ways: Optionally, the switch switching device adopts an iterative learning control strategy, uses the experience accumulated during multiple switching processes to establish an association model between the characteristic parameters and the control parameters, and continuously optimizes the parameter configuration through the gradient descent method; Optionally, the switch switching device can also adopt a neural network adaptive control method to online learn the dynamic characteristics of the switching process and adjust the control parameters in real time to improve the system performance. It can be understood that other optimization methods can also be used to achieve the adjustment of the control parameters, which are not limited here.

[0119] In some embodiments, the switch switching device calculates the deviation values of the overshoot, adjustment time, and steady-state error of the transient response waveform respectively with the corresponding performance indicators; determines the initial adjustment directions of the voltage adjustment coefficient, frequency adjustment coefficient, and phase adjustment coefficient according to the positive and negative signs of each deviation value; iteratively adjusts the dynamic control parameters according to the preset step size, and records the new transient response characteristics after each adjustment; if the adjusted characteristic parameters are better than those before adjustment, keep the current adjustment direction unchanged and increase the step size by a preset growth coefficient; if the adjusted characteristic parameters are worse than those before adjustment, reverse the adjustment direction and decrease the step size by a preset reduction coefficient; count the adjustment effects of a preset number. When the adjustment direction continuously changes or the step size is less than the minimum threshold, record the corresponding adjusted dynamic control parameters.

[0120] Among them, the deviation value represents the degree to which the characteristic parameter exceeds the target range and is used to determine the adjustment direction; the adjustment direction refers to the increasing or decreasing trend of parameter modification and guides the progress of the optimization process; the preset step size represents the amplitude of each adjustment and affects the convergence speed of the optimization process; the growth coefficient and the reduction coefficient respectively represent the proportional factors for step size adjustment and are used for adaptive control of the optimization process.

[0121] After the switch switching device discovers that the characteristic parameter exceeds the standard, it needs to optimize the dynamic control parameters. Specifically, the switch switching device first calculates the deviation value of the characteristic parameter and determines the initial adjustment direction according to the positive and negative of the deviation. Then it adopts an iterative optimization strategy with a variable step size, increases the step size to accelerate convergence when the adjustment effect is good, and decreases the step size and changes the direction when the adjustment effect becomes worse. Finally, it determines the final parameter configuration through termination conditions such as continuous adjustment direction change or too small step size.

[0122] It should be noted that the parameter optimization adopts an iterative algorithm with an adaptive step size. The initial step size is set to 5% of the normal working range of the corresponding parameter. The step size adjustment adopts an exponential decay mechanism, with a growth coefficient of 1.2 and a reduction coefficient of 0.8. This ensures both rapid convergence in the initial stage of optimization and fine adjustment when approaching the optimal solution. After each parameter adjustment, the improvement degree of the switching evaluation index is calculated to judge the adjustment effect. To ensure the convergence and real-time performance of the optimization process, the maximum number of iterations is set to 20 times. If the adjustment direction changes continuously for 3 times or the step size is less than 1% of the initial value, the iteration is terminated in advance. The entire optimization process balances the optimization speed and stability through dynamic adjustment coefficients and is applicable to different types of switching scenarios.

[0123] In some embodiments, parameter optimization can be achieved in various ways: Optionally, the switch switching device adopts a simulated annealing algorithm to perform random search in the parameter space, and controls the probability of accepting inferior solutions through temperature control parameters to avoid falling into local optimal solutions; Optionally, the switch switching device can also adopt a particle swarm optimization algorithm to search for the optimal parameter combination in parallel and improve the optimization efficiency through swarm intelligence. It can be understood that other optimization algorithms can also be used to adjust the control parameters, which are not limited here.

[0124] In the embodiments of the present application, due to the adoption of a dynamic adaptive control strategy based on historical data and real-time monitoring, a complete control system for disturbance level determination, parameter template selection, correction coefficient calculation, and characteristic parameter optimization is established. Combined with a comprehensive evaluation mechanism in three dimensions of voltage, frequency, and phase, the sampling period and control parameters can be adjusted in real time according to the grid state, realizing the intelligent optimization of the switching strategy. It effectively solves the problems of poor reliability and weak adaptability of traditional fixed parameter schemes in complex power supply environments, as well as the slow response of PID controllers under large disturbance conditions. It realizes the efficient and stable control of the switching process and significantly improves the reliability of the power supply system.

[0125] The switch switching device in the embodiments of the present invention application will be described from the perspective of hardware processing below. Please refer to Figure 3 , which is a schematic structural diagram of an entity device of the switch switching device in the embodiments of the present application.

[0126] It should be noted that Figure 3 The structure of the switch switching device shown is only an example and should not bring any limitations to the functions and usage ranges of the embodiments of the present invention.

[0127] Such as Figure 3As shown, the switch switching device includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the Read-Only Memory (ROM) 302 or the program loaded from the storage section 308 into the Random Access Memory (RAM) 303, such as executing the method described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0128] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a Liquid Crystal Display (LCD), an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read from it can be installed into the storage section 308 as needed.

[0129] Specifically, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the Central Processing Unit (CPU) 301, various functions defined in the present invention are executed.

[0130] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings.

[0132] Specifically, the switch switching device of this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the switching method of the primary-secondary integrated switch provided in the above embodiment is implemented.

[0133] On the other hand, the present invention also provides a computer-readable storage medium, which may be included in the switch switching device described in the above embodiment; or it may exist separately without being assembled into the switch switching device. The above storage medium carries one or more computer programs. When the above one or more computer programs are executed by a processor of the switch switching device, the switch switching device is enabled to implement the switching method of the primary-secondary integrated switch provided in the above embodiment.

[0134] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present application.

[0135] As used in the foregoing embodiments, depending on the context, the term "when" may be construed to mean "if" or "after" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "upon determining" or "if (the stated condition or event) is detected" may be construed to mean "if determined" or "in response to determining" or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".

[0136] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the foregoing embodiments can be implemented. The processes can be completed by relevant hardware instructed by a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the foregoing method embodiments. The foregoing storage medium includes: various media such as ROM or random access memory RAM, magnetic disk, or optical disc that can store program codes.

Claims

1. A switching method of a primary and secondary fusion switch, characterized in that: Applied to a switch switching device, the method comprises: Obtain real-time and historical electrical parameters of the operating power supply; Determining a system disturbance level based on a rate of change of the real-time electrical parameter relative to the historical electrical parameter, and determining a system sampling period according to the system disturbance level; the system sampling period is inversely proportional to the system disturbance level; Collecting target electrical parameters of the power supply to be switched in during the system sampling period, and calculating a switching evaluation index according to the real-time electrical parameters and the target electrical parameters; the switching evaluation index includes a voltage amplitude deviation coefficient, a frequency stability coefficient, and a phase matching coefficient; Determining the dynamic control parameters of the power source to be switched in according to the switching evaluation index and the system disturbance level; When the adjustment rate of the dynamic control parameter is greater than a first preset threshold and the switching evaluation index is less than a second preset threshold, generating a switching enable signal; The primary and secondary fusion switches are controlled to perform a switching operation according to the switching enable signal.

2. The method according to claim 1, characterized in that The step of determining the system disturbance level based on the rate of change of the real-time electrical parameter relative to the historical electrical parameter, and determining the system sampling period according to the system disturbance level specifically includes: Obtain multiple sets of historical electrical parameter samples within a preset time window; Performing sliding average filtering on the multiple groups of historical electrical parameter samples to obtain benchmark electrical parameters; Calculating the voltage change rate, frequency change rate and phase change rate of the real-time electrical parameter relative to the reference electrical parameter; Comparing the voltage change rate, frequency change rate and phase change rate with the corresponding disturbance level determination thresholds respectively to obtain numerical comparison results; According to the numerical comparison result, the highest disturbance level is determined from a plurality of preset disturbance levels as the system disturbance level; the determination threshold of the disturbance level increases as the disturbance level increases; A system sampling period is determined according to the system disturbance level.

3. The method according to claim 1, characterized in that The step of collecting the target electrical parameters of the power supply to be switched in the system sampling period, and calculating the switching evaluation index according to the real-time electrical parameters and the target electrical parameters, specifically includes: Collecting target electrical parameters of the power supply to be switched in during the system sampling period; Extracting an effective value of an operating voltage, an operating frequency, and an operating phase angle from the real-time electrical parameters, and extracting an effective value of a target voltage, a target frequency, and a target phase angle from the target electrical parameters; Calculate a voltage amplitude deviation coefficient based on the operating voltage effective value and the target voltage effective value, calculate a frequency stability coefficient based on the operating frequency and the target frequency, and calculate a phase matching coefficient based on the operating phase angle and the target phase angle; The weight coefficients for matching the voltage amplitude deviation coefficient, the frequency stability coefficient and the phase matching coefficient are determined, and a switching evaluation index is obtained by weighted calculation.

4. The method according to claim 1, characterized in that: Before the step of determining the dynamic control parameters of the power source to be switched in according to the switching evaluation index and the system disturbance level, the method further includes: Selecting initial control parameters from a plurality of preset control parameter templates based on the system disturbance level; Calculating a correction coefficient of each parameter in the initial control parameter according to the switching evaluation index; The dynamic control parameters of the power supply to be switched in are determined according to the initial control parameters and the corresponding correction coefficients; the control parameters include a voltage adjustment coefficient, a frequency adjustment coefficient and a phase adjustment coefficient; the correction coefficient and the switching evaluation index satisfy an exponential function relationship, and the correction coefficient decays exponentially with the increase of the switching evaluation index.

5. The method according to claim 4, characterized in that The step of determining the dynamic control parameters of the power source to be switched in according to the initial control parameters and the corresponding correction coefficients specifically includes: The system disturbance level, the switching evaluation index and the historical switching data including the overshoot, the adjustment time and the steady-state error are used as training samples, and a polynomial regression method is used to train and generate a correction coefficient model; the order of the regression polynomial of the polynomial regression method does not exceed the third order; Based on the correction coefficient model, determining a reference value matrix of the correction coefficient; the reference value matrix includes a voltage correction coefficient, a frequency correction coefficient and a phase correction coefficient; According to the reference value matrix, the statistical distribution characteristics of each correction coefficient under different disturbance levels are calculated, and a piecewise linear regression model is constructed based on the statistical distribution characteristics; the statistical distribution characteristics include mean, variance and skewness; Inputting the system disturbance level and the switching evaluation index into the piecewise linear regression model to obtain a real-time correction coefficient; The dynamic control parameters of the power source to be switched in are calculated according to the real-time correction coefficient and the initial control parameters.

6. The method according to claim 1, characterized in that After the step of controlling the primary and secondary fusion switches to perform the switching operation according to the switching enable signal, the method further includes: Real-time monitoring of the transient response waveform of the primary and secondary fusion switch during the switching process; Extract characteristic parameters of the transient response waveform; the characteristic parameters include overshoot, adjustment time and steady-state error; When the characteristic parameter exceeds a preset performance indicator range, the dynamic control parameter is adjusted.

7. The method according to claim 6, characterized in that When the characteristic parameter exceeds the preset performance indicator range, the step of adjusting the dynamic control parameter specifically includes: Calculate deviation values ​​of the overshoot, adjustment time and steady-state error of the transient response waveform and the corresponding performance indicators respectively; According to the positive and negative signs of each deviation value, the initial adjustment direction of the voltage adjustment coefficient, the frequency adjustment coefficient and the phase adjustment coefficient is determined; Iteratively adjusting the dynamic control parameters according to a preset step size, and recording new transient response characteristics after each adjustment; If the characteristic parameter after adjustment is better than before adjustment, the current adjustment direction is kept unchanged and the step length is increased by the preset growth factor; if the characteristic parameter after adjustment is worse than before adjustment, the adjustment direction is reversed and the step length is reduced by the preset reduction factor; The preset number of adjustment effects are counted, and when the adjustment direction changes continuously or the step size is less than the minimum threshold, the corresponding dynamic control parameters after adjustment are recorded.

8. A switch switching device, characterized in that: The switch switching device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the switch switching device to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the switch device, the switch device is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product runs on a switch device, the switch device is caused to execute the method according to any one of claims 1 to 7.

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