Online interactive uninterruptible power supply state switching method and equipment thereof

Abstract

The invention relates to the technical field of energy management, and discloses an online interactive uninterruptible power supply state switching method and equipment thereof, and the method comprises the following steps: step S01, constructing uninterruptible power supply dual-mode switching constraint conditions, step S02, analyzing the electric energy storage state of dual-mode switching, quantifying the complexity of dual-mode switching, and determining the state of the uninterruptible power supply. S03, generating a disturbance parameter combination through Gaussian distribution disturbance, S04, carrying out multi-scene state switching simulation evaluation and collecting key indexes, and S05, constructing a three-dimensional effect display model, determining a final switching parameter array, and solidifying the final switching parameter array to a UPS control strategy. According to the online interactive uninterruptible power supply state switching method and device, the state switching performance of the online interactive uninterruptible power supply is remarkably improved, meanwhile, the intelligent level and the adaptive capacity are enhanced, intelligent upgrading of UPS switching control is achieved, and a brand new technical solution is provided for key electric power guarantee.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and more particularly to an online interactive uninterruptible power supply state switching method and device thereof. Background Art

[0002] With the continuous development of uninterruptible power supply (UPS) technology, line-interactive UPSs have gradually become key power supply devices for data centers, industrial equipment, and communication systems due to their advantages in load power supply reliability, power quality optimization, and flexible operating mode switching. However, existing line-interactive UPSs still have certain shortcomings in their state switching methods, especially in terms of switching speed, intelligent switching logic, and adaptability to complex operating conditions, making it difficult to fully meet the needs of modern application scenarios.

[0003] In the prior art, the patent "Uninterruptible Power Supply Input Abnormality Detection Method, System and Terminal Device" with publication number CN110829576B obtains the input source detection parameters and bus detection parameters of the uninterruptible power supply to determine whether the input source is in an oscillating state, and based on this, determines whether the input is abnormal, thereby achieving switching from main or bypass power supply to battery power supply. However, this technical solution mainly relies on the state detection of the input source and lacks a comprehensive analysis of the changes in load demand and the internal state of the power supply, which may lead to inaccurate switching decisions. In addition, this solution does not fully consider the optimization of switching time during the switching process, which may cause a brief power outage or performance degradation of the load in some application scenarios that are sensitive to switching time.

[0004] Another existing technology, patent publication number CN106155260B, "Server System and Management Method and Computer-Readable Storage Medium," achieves seamless power supply by determining the status of the AC input power supplied to the server system and dynamically managing the switching between offline and online modes of the uninterruptible power supply based on the power status. However, this technical solution is primarily designed for specific server system applications, and its switching logic is relatively simple, failing to fully consider adaptability to different load types and complex operating conditions.

[0005] The above issues indicate that existing state switching methods for online interactive uninterruptible power supplies (UPSs) still have certain deficiencies in terms of intelligent switching logic, optimized switching time, and adaptability to complex operating conditions. In modern applications, the diverse load demands and complex and changing external input conditions place higher demands on the UPS switching logic. Therefore, a new state switching method for online interactive uninterruptible power supplies is urgently needed. By comprehensively analyzing the internal state of the power supply, changes in load demand, and external input conditions, it optimizes the switching logic, shortens the switching time, and improves adaptability to complex operating conditions to meet the actual needs of efficient, intelligent UPSs. Summary of the Invention

[0006] In order to overcome the above-mentioned defects in the prior art, the present invention provides an online interactive uninterruptible power supply state switching method and device thereof to solve the problems existing in the above-mentioned background technology.

[0007] The present invention provides the following technical solution: a method for switching the state of an online interactive uninterruptible power supply, comprising the following steps: Step S01: Constructing the uninterruptible power supply dual-mode switching constraint conditions: Constructing the uninterruptible power supply dual-mode switching constraint conditions based on the voltage fluctuation range of the input power supply and the load of the UPS, and initializing the switching threshold of the dual-mode switching based on historical operation data; Step S02: Analyze the energy storage state of dual-mode switching and quantify the complexity of dual-mode switching: Analyze the energy storage state of dual-mode switching, establish the battery mode switching conditions when the mains power is abnormal, and quantify the switching complexity to calculate the switching complexity index; Step S03: Generate a disturbance parameter combination through Gaussian distribution perturbation: perform Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets; Step S04: Multi-scenario state switching simulation evaluation and key indicator collection: Simulate power grid failure and harmonic interference scenarios in a virtual load environment, apply different switching parameter arrays to perform state switching, and collect key indicators of the switching process: resource usage, delay data, and switching quality; Step S05: Construct a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy: correspond the collected key indicators to the switching parameter array, construct a three-dimensional effect display model, select the Pareto optimal solution through surface analysis, determine the final switching parameter array and solidify it into the UPS control strategy.

[0008] Preferably, the uninterruptible power supply dual-mode switching constraint condition is constructed based on the voltage fluctuation range of the input power supply and the load of the UPS, wherein the uninterruptible power supply dual-mode includes a mains mode and a battery mode, and the specific contents are as follows: Establish constraints for switching from mains mode to battery mode: preset an allowable fluctuation range of the mains mode input voltage, which includes a maximum allowable fluctuation range of the input voltage and a minimum allowable fluctuation range of the input voltage. When the voltage of the input power supply is lower than the minimum allowable fluctuation range or higher than the maximum allowable fluctuation range of the input voltage, the mains mode is switched to the battery mode. Establish constraints for switching from battery mode to mains mode: Perform hysteresis voltage analysis on the preset allowable fluctuation range of the input voltage in mains mode. The difference between the maximum allowable fluctuation range of the input voltage and the hysteresis voltage, and the difference between the minimum allowable fluctuation range of the input voltage and the hysteresis voltage, are used as the allowable fluctuation range of the input voltage. Establish constraints for switching from battery mode to mains mode. When the input power voltage is within the allowable fluctuation range, the battery mode is switched to mains mode. Constructing dual-mode comprehensive constraints: UPS rated output power Actual load power.

[0009] Preferably, the specific contents of analyzing the electric energy storage state of the dual-mode switching and quantifying the complexity of the dual-mode switching are as follows: Establish the conditions for switching into battery mode when the mains power is abnormal: Analyze the energy storage status in battery mode. If the actual available battery capacity meets the battery mode requirements, switch into battery mode when the mains power is abnormal. If the actual available battery capacity does not meet the battery mode requirements, do not switch into battery mode when the mains power is abnormal, and activate the safety mechanism; Quantifying the complexity of dual-mode switching and calculating the switching complexity index: Core evaluation dimensions are established, and the weights of the core evaluation dimensions are determined using the Analytic Hierarchy Process (AHP). The core evaluation dimensions include voltage transient intensity, load step amplitude, timing constraint strictness, energy storage state uncertainty, and protection response complexity. The range method is used to normalize each evaluation dimension to [0, 1], and a dynamic correction factor is introduced to calculate the switching complexity index.

[0010] Preferably, the specific content of performing Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets is as follows: Step S1: defining disturbance parameters according to an initial handover threshold and a handover complexity index, wherein the disturbance parameters include a handover threshold disturbance intensity and a handover complexity index disturbance intensity; Step S2: perturbing the initial handover threshold and the handover complexity index based on the Gaussian distribution function to generate a perturbed handover threshold and a perturbed handover complexity index; Step S3: combining the disturbed handover threshold and the handover complexity index to form N groups of handover parameter sets, each group of handover parameter sets including a handover threshold and a handover complexity index.

[0011] Preferably, the specific contents of simulating grid fault and harmonic interference scenarios in a virtual load environment and applying different switching parameter arrays to perform state switching are as follows: Build a virtual load environment: Use simulation software to build a virtual load environment similar to the actual load environment; Simulating grid fault scenarios: In a virtual load environment, grid voltage fault scenarios are simulated to test the UPS's response and switching capabilities under different grid faults, including grid voltage sags, swells, and outages. Simulate harmonic interference scenarios: In a virtual load environment, simulate harmonic interference in the power grid to test the stability and switching performance of the UPS under harmonic interference; Apply different switching parameter arrays for state switching: N groups of switching parameter sets are applied separately to perform state switching under simulated power grid fault and harmonic interference scenarios. Key indicators of the switching process are recorded, including resource usage, latency data, and switching quality.

[0012] Preferably, the specific contents of constructing a three-dimensional effect display model to determine the final switching parameter array and solidifying it into the UPS control strategy are as follows: The collected key indicators are matched with the switching parameter arrays to construct a three-dimensional effect display model: a three-dimensional coordinate system is constructed to show the impact of different switching parameter arrays on key indicators. The three dimensions of the three-dimensional coordinates represent resource usage, latency data, and switching quality, respectively. The evaluation results of different switching parameter arrays and their corresponding key indicator combinations are mapped into three-dimensional space. Each switching parameter array corresponds to a point. A surface consisting of points is drawn in the three-dimensional coordinate system using a surface fitting algorithm to obtain the three-dimensional effect display model. Selecting the Pareto optimal solution through surface analysis: In the 3D effect display model, by comparing the positions of corresponding points of different switching parameter arrays and combining them with the surface morphology, we select the peak areas in resource usage, delay data, and switching quality. The final switching parameter array is determined and solidified into the UPS control strategy. If resources are limited, the switching parameter array corresponding to the peak value in the area where the point with the lowest resource usage in the surface is located is selected as the selected switching parameter array; If the delay is sensitive, the switching parameter array corresponding to the peak in the area where the point with the lowest delay in the surface is located is selected as the selected switching parameter array; If quality is prioritized, the switching parameter array corresponding to the peak in the area where the point with the highest switching quality in the surface is located is selected as the selected switching parameter array.

[0013] Preferably, an online interactive uninterruptible power supply state switching device includes: a processor; and a computer program stored on and runnable on the processor; wherein, when the processor executes the computer program, an online interactive uninterruptible power supply state switching method is implemented.

[0014] Technical effects and advantages of the present invention: The present invention includes steps S01: constructing uninterruptible power supply dual-mode switching constraint conditions; step S02: analyzing the energy storage state of the dual-mode switching and quantifying the complexity of the dual-mode switching; step S03: generating a disturbance parameter combination through Gaussian distribution perturbation; step S04: multi-scenario state switching simulation evaluation and collection of key indicators; and step S05: constructing a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy. This improves the state switching performance of the online interactive uninterruptible power supply and realizes the intelligent upgrade of UPS switching control. Through multi-scenario state switching simulation evaluation, the system monitors the grid status, load demand, and internal status of the power supply in real time, and intelligently adjusts the switching logic and parameters to adapt to complex and changing operating conditions. In the event of grid voltage sag, swell, or interruption, the system can respond quickly to ensure that the UPS smoothly switches to the backup power source, guaranteeing the continuity and stability of the load power supply. At the same time, when facing power quality issues such as harmonic interference, the system can also effectively evaluate the UPS switching performance, optimize the switching strategy, and reduce the impact of harmonics on the load. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The figure is a flow chart of a method for switching the state of an online interactive uninterruptible power supply. DETAILED DESCRIPTION

[0016] The technical solutions of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The online interactive uninterruptible power supply state switching method and device involved in the present invention are not limited to the various structures described in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative efforts fall within the scope of protection of the present invention.

[0017] like Figure 1 As shown, the present invention provides an online interactive uninterruptible power supply state switching method, comprising the following steps: Step S01: Constructing the uninterruptible power supply dual-mode switching constraint conditions: Constructing the uninterruptible power supply dual-mode switching constraint conditions based on the voltage fluctuation range of the input power supply and the load of the UPS, and initializing the switching threshold of the dual-mode switching based on historical operation data; Step S02: Analyze the energy storage state of dual-mode switching and quantify the complexity of dual-mode switching: Analyze the energy storage state of dual-mode switching, establish the battery mode switching conditions when the mains power is abnormal, and quantify the switching complexity to calculate the switching complexity index; Step S03: Generate a disturbance parameter combination through Gaussian distribution perturbation: perform Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets; Step S04: Multi-scenario state switching simulation evaluation and key indicator collection: Simulate power grid failure and harmonic interference scenarios in a virtual load environment, apply different switching parameter arrays to perform state switching, and collect key indicators of the switching process: resource usage, delay data, and switching quality; Step S05: Construct a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy: correspond the collected key indicators to the switching parameter array, construct a three-dimensional effect display model, select the Pareto optimal solution through surface analysis, determine the final switching parameter array and solidify it into the UPS control strategy.

[0018] In this embodiment, it should be specifically explained that, according to the voltage fluctuation range of the input power supply and the load of the UPS (uninterruptible power supply), the uninterruptible power supply dual-mode switching constraint condition is constructed, wherein the uninterruptible power supply dual-mode includes a mains mode and a battery mode. The specific contents are as follows: Establish constraints for switching from mains mode to battery mode: preset an allowable fluctuation range of the mains mode input voltage, which includes a maximum allowable fluctuation range of the input voltage and a minimum allowable fluctuation range of the input voltage. When the voltage of the input power supply is lower than the minimum allowable fluctuation range or higher than the maximum allowable fluctuation range of the input voltage, the mains mode is switched to the battery mode. Establish constraints for switching from battery mode to mains mode: Perform hysteresis voltage analysis on the preset allowable fluctuation range of the input voltage in mains mode. The difference between the maximum allowable fluctuation range of the input voltage and the hysteresis voltage, and the difference between the minimum allowable fluctuation range of the input voltage and the hysteresis voltage, are used as the allowable fluctuation range of the input voltage. Establish constraints for switching from battery mode to mains mode. When the input power voltage is within the allowable fluctuation range, the battery mode is switched to mains mode. Constructing dual-mode comprehensive constraints: UPS rated output power Actual load power.

[0019] In this embodiment, it should be specifically explained that the specific contents of analyzing the electric energy storage state of the dual-mode switching and quantifying the complexity of the dual-mode switching are as follows: Establish the conditions for switching into battery mode when the mains power is abnormal: Analyze the energy storage status in battery mode. If the actual available battery capacity meets the battery mode requirements, switch into battery mode when the mains power is abnormal. If the actual available battery capacity does not meet the battery mode requirements, do not switch into battery mode when the mains power is abnormal, and activate the safety mechanism; Quantifying the complexity of dual-mode switching and calculating the switching complexity index: Core evaluation dimensions were established and weighted using the Analytic Hierarchy Process (AHP). The core evaluation dimensions included voltage transient intensity, load step amplitude, timing constraint strictness, energy storage state uncertainty, and protection response complexity. The range method was used to normalize each evaluation dimension to [0, 1], and a dynamic correction factor was introduced to calculate the switching complexity index. Voltage transient intensity is used to measure the degree of voltage fluctuation during the switching process, reflecting the system's control capability requirements for voltage stability; load step amplitude indicates the degree of sudden change in load during switching, affecting the system's dynamic response and stability; timing constraint strictness reflects the requirements for time sequence and timing accuracy during the switching process, such as certain operations must be completed within a specific time; energy storage state uncertainty is used to evaluate the state uncertainty of energy storage devices during switching, including changes in parameters such as power and internal resistance; protection response complexity is used to measure the response complexity of the protection system during the switching process, including the triggering conditions, logical judgment and execution speed of the protection action; The switching complexity is used as the target layer and the five core evaluation dimensions are used as the criterion layer to construct the judgment matrix. The maximum eigenvalue and the corresponding eigenvector of the judgment matrix are calculated and normalized to obtain the weight value of each criterion layer. Calculate the normalized value based on the maximum and minimum values in each evaluation dimension: Use the formula Normalize the original data, represents the normalized value, Represents the original value, and Represent the maximum and minimum values respectively; In order to more accurately reflect the switching complexity, a dynamic correction factor k is introduced to consider the dynamic changes and uncertainties in the actual switching process. The dynamic correction factor can be adjusted according to actual conditions, such as switching speed, environmental conditions, and other factors. Combining the above evaluation dimensions and correction factors, the calculation formula of the switching complexity index is expressed as: ,in represents the switching complexity index, represents the normalized value of voltage transient intensity, represents the normalized value of the load step amplitude, represents the normalized value of timing constraint strictness, represents the normalized value of energy storage state uncertainty, represents the normalized value of protection response complexity, 、 、 、 as well as Represent the weight of each evaluation dimension.

[0020] In this embodiment, it should be specifically explained that the specific content of performing Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets is as follows: Step S1: Based on the initial switching threshold and switching complexity index Define disturbance parameters, including switching threshold disturbance intensity and switching complexity exponential perturbation intensity ; Step S2: perturbing the initial handover threshold and the handover complexity index based on the Gaussian distribution function to generate a perturbed handover threshold and a perturbed handover complexity index; Switching threshold after disturbance ,in , where N represents the number of handover parameter sets; Switching complexity index after disturbance ,in ; Step S3: combining the disturbed handover threshold and the handover complexity index to form N groups of handover parameter sets, each group of handover parameter sets including a handover threshold and a handover complexity index; When the initial switching threshold , switching complexity index , switching threshold disturbance intensity and switching complexity exponential perturbation intensity When , 5 sets of parameters are generated, the possible outputs are: 、 、 、 as well as .

[0021] In this embodiment, it should be specifically explained that the specific contents of simulating grid fault and harmonic interference scenarios in a virtual load environment and applying different switching parameter arrays to perform state switching are as follows: Build a virtual load environment: Use simulation software to build a virtual load environment similar to the actual load environment; Simulating grid fault scenarios: In a virtual load environment, grid voltage fault scenarios are simulated to test the UPS's response and switching capabilities under different grid faults, including grid voltage sags, swells, and outages. Simulate harmonic interference scenarios: In a virtual load environment, simulate harmonic interference in the power grid to test the stability and switching performance of the UPS under harmonic interference; Apply different switching parameter arrays for state switching: N groups of switching parameter sets are applied separately to perform state switching under simulated power grid fault and harmonic interference scenarios. Key indicators of the switching process are recorded, including resource usage, latency data, and switching quality.

[0022] In this embodiment, it should be specifically explained that the specific contents of constructing the three-dimensional effect display model to determine the final switching parameter array and solidifying it into the UPS control strategy are as follows: The collected key indicators are matched with the switching parameter arrays to construct a three-dimensional effect display model: a three-dimensional coordinate system is constructed to show the impact of different switching parameter arrays on key indicators. The three dimensions of the three-dimensional coordinates represent resource usage, latency data, and switching quality, respectively. The evaluation results of different switching parameter arrays and their corresponding key indicator combinations are mapped into three-dimensional space. Each switching parameter array corresponds to a point. A surface consisting of points is drawn in the three-dimensional coordinate system using a surface fitting algorithm to obtain the three-dimensional effect display model. Selecting the Pareto optimal solution through surface analysis: In the 3D effect display model, by comparing the positions of corresponding points of different switching parameter arrays and combining them with the surface morphology, we select the peak areas in resource usage, delay data, and switching quality. The final switching parameter array is determined and solidified into the UPS control strategy. If resources are limited, the switching parameter array corresponding to the peak value in the area where the point with the lowest resource usage in the surface is located is selected as the selected switching parameter array; If the delay is sensitive, the switching parameter array corresponding to the peak in the area where the point with the lowest delay in the surface is located is selected as the selected switching parameter array; If quality is prioritized, the switching parameter array corresponding to the peak in the area where the point with the highest switching quality in the surface is located is selected as the selected switching parameter array.

[0023] In this embodiment, it should be specifically explained that an online interactive uninterruptible power supply state switching device includes: a processor; and a computer program stored on and executable on the processor; wherein, when the processor executes the computer program, an online interactive uninterruptible power supply state switching method is implemented.

[0024] The main difference between this embodiment and the prior art is that this embodiment includes step S01: constructing uninterruptible power supply dual-mode switching constraint conditions, step S02: analyzing the energy storage state of dual-mode switching and quantifying the complexity of dual-mode switching, step S03: generating a disturbance parameter combination through Gaussian distribution perturbation, step S04: multi-scenario state switching simulation evaluation and collection of key indicators, and step S05: constructing a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy, thereby improving the state switching performance of the online interactive uninterruptible power supply and realizing the intelligent upgrade of UPS switching control; Through multi-scenario state switching simulation evaluation, the system monitors the grid status, load demand, and internal status of the power supply in real time, and intelligently adjusts the switching logic and parameters to adapt to complex and changing operating conditions. In the event of grid voltage sag, swell, or interruption, the system can respond quickly to ensure that the UPS smoothly switches to the backup power source, guaranteeing the continuity and stability of the load power supply. At the same time, when facing power quality issues such as harmonic interference, the system can also effectively evaluate the UPS switching performance, optimize the switching strategy, and reduce the impact of harmonics on the load.

[0025] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0026] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for switching states of an online interactive uninterruptible power supply, characterized by: The following steps are involved: Step S01: Constructing the uninterruptible power supply dual-mode switching constraint conditions: Constructing the uninterruptible power supply dual-mode switching constraint conditions based on the voltage fluctuation range of the input power supply and the load of the UPS, and initializing the switching threshold of the dual-mode switching based on historical operation data; Step S02: Analyze the energy storage state of dual-mode switching and quantify the complexity of dual-mode switching: Analyze the energy storage state of dual-mode switching, establish the battery mode switching conditions when the mains power is abnormal, and quantify the switching complexity to calculate the switching complexity index; Step S03: Generate a disturbance parameter combination through Gaussian distribution perturbation: perform Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets; Step S04: Multi-scenario state switching simulation evaluation and key indicator collection: Simulate power grid failure and harmonic interference scenarios in a virtual load environment, apply different switching parameter arrays to perform state switching, and collect key indicators of the switching process: resource usage, delay data, and switching quality; Step S05: Construct a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy: correspond the collected key indicators to the switching parameter array, construct a three-dimensional effect display model, select the Pareto optimal solution through surface analysis, determine the final switching parameter array and solidify it into the UPS control strategy.

2. The method for switching states of an online interactive uninterruptible power supply according to claim 1, wherein: According to the voltage fluctuation range of the input power supply and the load of the UPS, the uninterruptible power supply dual-mode switching constraint condition is constructed, and the uninterruptible power supply dual mode includes the mains mode and the battery mode. The specific content is as follows: Establish constraints for switching from mains mode to battery mode: preset an allowable fluctuation range of the mains mode input voltage, which includes a maximum allowable fluctuation range of the input voltage and a minimum allowable fluctuation range of the input voltage. When the voltage of the input power supply is lower than the minimum allowable fluctuation range or higher than the maximum allowable fluctuation range of the input voltage, the mains mode is switched to the battery mode. Establish constraints for switching from battery mode to mains mode: Perform hysteresis voltage analysis on the preset allowable fluctuation range of the input voltage in mains mode. The difference between the maximum allowable fluctuation range of the input voltage and the hysteresis voltage, and the difference between the minimum allowable fluctuation range of the input voltage and the hysteresis voltage, are used as the allowable fluctuation range of the input voltage. Establish constraints for switching from battery mode to mains mode. When the input power voltage is within the allowable fluctuation range, the battery mode is switched to mains mode. Constructing dual-mode comprehensive constraints: UPS rated output power Actual load power.

3. The method for switching states of an online interactive uninterruptible power supply according to claim 1, wherein: The specific contents of analyzing the energy storage state of dual-mode switching and quantifying the complexity of dual-mode switching are as follows: Establish the conditions for switching into battery mode when the mains power is abnormal: Analyze the energy storage status in battery mode. If the actual available battery capacity meets the battery mode requirements, switch into battery mode when the mains power is abnormal. If the actual available battery capacity does not meet the battery mode requirements, do not switch into battery mode when the mains power is abnormal, and activate the safety mechanism; Quantify the complexity of dual-mode switching and calculate the switching complexity index: establish core evaluation dimensions and use the AHP analytical hierarchy process to determine the weights of the core evaluation dimensions. The core evaluation dimensions include: voltage transient intensity, load step amplitude, timing constraint strictness, energy storage state uncertainty, and protection response complexity. The range method is used to normalize each evaluation dimension to [0, 1], and a dynamic correction factor is introduced to calculate the switching complexity index.

4. The method for switching states of an online interactive uninterruptible power supply according to claim 1, wherein: The specific contents of performing Gaussian distribution perturbation on the initial handover threshold and the handover complexity index to generate N groups of handover parameter sets are as follows: Step S1: defining disturbance parameters according to an initial handover threshold and a handover complexity index, wherein the disturbance parameters include a handover threshold disturbance intensity and a handover complexity index disturbance intensity; Step S2: perturbing the initial handover threshold and the handover complexity index based on the Gaussian distribution function to generate a perturbed handover threshold and a perturbed handover complexity index; Step S3: combining the disturbed handover threshold and the handover complexity index to form N groups of handover parameter sets, each group of handover parameter sets including a handover threshold and a handover complexity index.

5. The method for switching states of an online interactive uninterruptible power supply according to claim 1, wherein: The specific contents of simulating grid fault and harmonic interference scenarios in a virtual load environment and applying different switching parameter arrays to perform state switching are as follows: Build a virtual load environment: Use simulation software to build a virtual load environment similar to the actual load environment; Simulating grid fault scenarios: In a virtual load environment, grid voltage fault scenarios are simulated to test the UPS's response and switching capabilities under different grid faults, including grid voltage sags, swells, and outages. Simulate harmonic interference scenarios: In a virtual load environment, simulate harmonic interference in the power grid to test the stability and switching performance of the UPS under harmonic interference; Apply different switching parameter arrays for state switching: N groups of switching parameter sets are applied separately to perform state switching under simulated power grid fault and harmonic interference scenarios. Key indicators of the switching process are recorded, including resource usage, latency data, and switching quality.

6. The method for switching states of an online interactive uninterruptible power supply according to claim 1, wherein: The specific contents of constructing a three-dimensional effect display model to determine the final switching parameter array and solidify it into the UPS control strategy are as follows: The collected key indicators are matched with the switching parameter arrays to construct a three-dimensional effect display model: a three-dimensional coordinate system is constructed to show the impact of different switching parameter arrays on key indicators. The three dimensions of the three-dimensional coordinates represent resource usage, latency data, and switching quality, respectively. The evaluation results of different switching parameter arrays and their corresponding key indicator combinations are mapped into three-dimensional space. Each switching parameter array corresponds to a point. A surface consisting of points is drawn in the three-dimensional coordinate system using a surface fitting algorithm to obtain the three-dimensional effect display model. Selecting the Pareto optimal solution through surface analysis: In the 3D effect display model, by comparing the positions of corresponding points of different switching parameter arrays and combining them with the surface morphology, we select the peak areas in resource usage, delay data, and switching quality. The final switching parameter array is determined and solidified into the UPS control strategy. If resources are limited, the switching parameter array corresponding to the peak value in the area where the point with the lowest resource usage in the surface is located is selected as the selected switching parameter array; If the delay is sensitive, the switching parameter array corresponding to the peak in the area where the point with the lowest delay in the surface is located is selected as the selected switching parameter array; If quality is prioritized, the switching parameter array corresponding to the peak in the area where the point with the highest switching quality in the surface is located is selected as the selected switching parameter array.

7. An online interactive uninterruptible power supply state switching device, characterized in that: The online interactive uninterruptible power supply state switching device includes: a processor; and a computer program stored on and runnable on the processor; wherein, when the processor executes the computer program, an online interactive uninterruptible power supply state switching method according to any one of claims 1 to 6 is implemented.

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