Uninterruptible power supply method and system based on ATSE and UPS

Abstract

The invention discloses an ATSE and UPS-based uninterruptible power supply method and system, and relates to the technical field of uninterruptible power supplies, and the method comprises the steps: obtaining a power supply state of a power utilization end, and obtaining a corresponding recommendation factor according to a real-time multi-dimensional factor value and a real-time weight; establishing a used time resource pool, and distributing the maximum working used time of each sub-module to the used time resource pool; acquiring a power utilization end characteristic index, and selecting the sub-modules according to the power utilization end characteristic index, the recommendation factors of the sub-modules and the used time resource pool to form a plurality of power supply sequences; the total switching time of the sub-modules in each power supply sequence is calculated, and the power supply sequence with the minimum total switching time is marked as an initial power supply sequence; by monitoring the power supply state in real time and dynamically adjusting the sub-module recommendation factors, the power supply sequence with the minimum total switching time is selected as the optimal power supply sequence, the power supply continuity is improved, the effect of improving the power supply efficiency is achieved, and the flexibility and adaptability of the system are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of uninterruptible power supplies, and particularly to an uninterruptible power supply method and system based on an ATSE and a UPS. Background Art

[0002] An ATSE is an automatic transfer switch that can automatically switch a load from one power source to another in case of a power failure; a UPS power supply is an uninterruptible power supply, which is a power supply device that converts the direct current output by a storage battery into alternating current to continuously supply power when the normal alternating current power supply is interrupted. It is mainly used to provide uninterrupted power supply for a single computer, a computer network system or other power electronic devices.

[0003] When the mains power fails due to an accident and is interrupted, the UPS immediately uses the electric energy of the battery in the machine and selects a new power source through an inverter conversion method to continue supplying power to the load, enabling the load to maintain normal operation and protecting the load software and hardware from damage. Since the power stored in a single uninterruptible power supply is limited, there is an easy problem of being unable to meet the power consumption requirements of the load.

[0004] The Chinese invention patent with the application number 202210831594.5 provides an uninterruptible power supply control method for continuous power supply, which obtains the mains power supply state; if the mains power supply state is a power supply interruption state, it obtains modular power supply information, and the modular power supply information includes multiple sub-module power source identifiers; according to the sub-module power source identifiers, it generates a power supply sequence; according to the power supply sequence, it generates a power supply control instruction and executes it.

[0005] However, in the prior art, only sub-modules are selected based on voltage anomalies and the power supply sequence is set. The power supply sequence is set by a single factor, with low flexibility; and when selecting the power supply sequence, the switching time generated between sub-modules is not considered, which further increases the power supply time and reduces the power supply efficiency. Summary of the Invention

[0006] The present application provides an uninterruptible power supply method and system based on an ATSE and a UPS, which solves the problem of reduced power supply efficiency due to increased power supply time in the prior art, and realizes the technical effects of reducing the total switching time between sub-modules during the power supply process, improving the power supply efficiency and stability.

[0007] The present application provides an uninterruptible power supply method and system based on an ATSE and a UPS, and the method includes:

[0008] S100: Obtain the power supply status of the power consumption end. If the power supply status is a power interruption status, extract the multi-dimensional data factor indicators of each sub-module according to the real-time data, and set the real-time multi-dimensional data factor values respectively. Obtain the corresponding recommendation factors according to the real-time multi-dimensional factor values and real-time weights; establish a time resource pool, and allocate the maximum working time of each sub-module to the time resource pool;

[0009] S200: Obtain the characteristic indicators of the power consumption end, and select sub-modules according to the characteristic indicators of the power consumption end, the recommendation factors of each sub-module, and the time resource pool to form multiple power supply sequences;

[0010] S300: Calculate the total switching time of the sub-modules in each power supply sequence, and mark the power supply sequence with the minimum switching total time as the initial power supply sequence.

[0011] Further, the method further includes: S400: Obtain the initial power supply sequence, and calculate the optimal switching time of each sub-module according to the voltage matching mechanism; determine the actual charge of each sub-module according to the optimal switching time of each sub-module;

[0012] S410: Adjust the power supply time of the initial power supply sequence based on the optimal switching time and the actual charge to form the optimal power supply sequence.

[0013] Further, the voltage matching mechanism is set as: Monitor the output voltage waveform and phase of each sub-module in real time to obtain voltage values and phase information;

[0014] Preset a voltage difference threshold and a phase difference threshold, and calculate the voltage difference and phase difference of any adjacent sub-modules at each time point according to the voltage values and phase information of each sub-module;

[0015] Select the time points corresponding to the voltage difference and phase difference that simultaneously satisfy the voltage difference threshold and the phase difference threshold, and use them as the preliminary switching time point candidate set;

[0016] Obtain the switching time point candidate set, form a fluctuation curve according to the time series, preliminarily divide time windows for the fluctuation curve, calculate the smoothness within each time window respectively, and select the time window with the highest smoothness as the candidate curve;

[0017] Evaluate the stability value of each time point in the candidate curve, and set the time point with the highest stability value as the optimal switching time.

[0018] Further, the method further includes: S500: Detect the repeated sub-modules in different optimal power supply sequences and mark them as the same sub-modules;

[0019] Collect the output voltage waveforms, phases, and optimal switching times of all power supply sequence sub-modules in real time, and mark the optimal switching times of the same sub-module in different power supply sequences as phase analysis nodes;

[0020] Calculate the compensation difference at the phase analysis nodes. If the compensation difference is greater than the preset compensation threshold, calculate the adjusted switching time;

[0021] Taking the same sub-module as a node and the edge weight as the phase compensation cost, construct a directed graph and identify the phase coordination relationship across power supply sequences;

[0022] S510: Establish a numerical evaluation model for switching times, obtain scoring factors, and select the adjustment plan with the largest scoring factor for adjustment and optimization.

[0023] Furthermore, the numerical evaluation model for switching times is based on the phase coordination relationship to obtain the index values of three indicators: switching efficiency, subsequent influence degree, and stability coefficient, and comprehensively calculate the scoring factor according to the index values of the three indicators; the calculation formula is as follows:

[0024]

[0025] Among them, Score is the scoring factor, E is the switching efficiency, I is the subsequent influence degree, S is the stability coefficient, and α, β, and γ are the preset corresponding weight coefficients respectively.

[0026] Furthermore, according to the real-time multi-dimensional data factor values and the preset initial weights, obtain the real-time weights, including:

[0027] Pre-construct a dynamic weight model and set the initial weights, obtain multiple historical multi-dimensional data factor values corresponding to the initial weights, and respectively obtain the ratios of the real-time multi-dimensional data factor values to the historical multi-dimensional data factor values. Adjust the initial weights according to the ratios, and set the adjusted initial weights as the real-time weights.

[0028] Furthermore, the multi-dimensional data factor indicators include voltage status, capacity margin, historical reliability, rated power, and working efficiency; the power consumption end characteristic indicators include the power demand, voltage demand, and power consumption period of the power consumption end.

[0029] Furthermore, the total switching time includes the ATSE action time, sub-module start-up delay, and path switching delay. The ATSE action time refers to the time from issuing the switching instruction to the contact closing; the sub-module start-up delay refers to the time from the sub-module receiving the power supply instruction to the stable output; the path switching delay refers to the switching time between different paths in multiple parallel power supply paths.

[0030] Further, the method further includes: S511: Classify sub-modules according to the factor index set of sub-modules, and classify the power consumption ends according to the factor index set of the power consumption ends, and divide them into high level, medium level and low level respectively; calculate the module level score of the same sub-module and the power consumption level score of the corresponding power consumption end;

[0031] S512: Obtain a level adjustment coefficient based on the module level score and the power consumption level score, adjust the scoring factor based on the level adjustment coefficient, and select the adjustment scheme corresponding to the largest adjusted scoring factor for adjustment and optimization.

[0032] An uninterruptible power supply system based on an ATSE and a UPS, the system includes:

[0033] A status monitoring and data analysis module, which is used to monitor the power supply status of the power consumption end in real time, extract the multi-dimensional data factor indexes of each sub-module, and calculate the real-time multi-dimensional data factor values; pre-construct a dynamic weight model, set the initial weight, and adjust the initial weight to the real-time weight according to the real-time multi-dimensional data factor values; calculate the recommendation factor according to the real-time multi-dimensional data factor values and the real-time weight; establish a time resource pool and allocate the maximum working time of each sub-module;

[0034] A power supply order generation module, which is used to obtain the power consumption end characteristic indexes, and select sub-modules to form multiple power supply orders according to the power consumption end characteristic indexes, the recommendation factors of each sub-module and the time resource pool; calculate the total switching time of the sub-modules in each power supply order, and select the power supply order with the smallest switching total time as the initial power supply order;

[0035] An optimal switching time calculation module, which is used to calculate the voltage difference and phase difference by monitoring the output voltage waveform and phase of each sub-module in real time according to the voltage matching mechanism, select the time points that meet the voltage difference threshold and phase difference threshold as the preliminary switching time point candidate set, evaluate the time points in the candidate curve, and determine the optimal switching time; adjust the initial power supply order according to the optimal switching time and the actual charge amount to form the optimal power supply order;

[0036] A power supply adjustment and optimization module, which is used to detect the repeated sub-modules in different optimal power supply orders and mark them as the same sub-module, collect the output voltage waveforms, phases and optimal switching times of the sub-modules in all power supply orders in real time for phase analysis; establish a switching time numerical evaluation model, comprehensively calculate the switching efficiency, subsequent influence degree and stability coefficient to obtain a scoring factor, and select the adjustment scheme with the largest scoring factor for adjustment and optimization;

[0037] A level division module, which is used to divide the sub-modules according to the factor index set of the sub-modules, and divide the power consumption ends according to the factor index set of the power consumption ends.

[0038] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0039] By monitoring the power supply status in real time and dynamically adjusting the sub-module recommendation factors, it is possible to quickly respond to power outages, select the power supply order with the minimum total switching time as the optimal power supply order, improve power supply continuity, and achieve the effect of improving power supply efficiency; establish a time resource pool, and reasonably allocate the maximum working time according to the capacity margin of the sub-module and the load power to ensure the efficient use of resources; based on multi-dimensional data factor indicators and dynamic weight adjustment, it can adapt to the needs of different power consumption ends and the state changes of sub-modules, and enhance the flexibility and adaptability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic flowchart of an uninterruptible power supply method based on ATSE and UPS in an embodiment of the present invention;

[0041] Figure 2 It is an architecture diagram of an uninterruptible power supply system based on ATSE and UPS in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] In order to facilitate the understanding of the present invention, the present application will be described more comprehensively with reference to the relevant drawings; the preferred embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs; the terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0044] Embodiment 1: As Figure 1 shown, an uninterruptible power supply method based on ATSE and UPS, the method includes:

[0045] S100: Obtain the power supply status of the power consumption end. If the power supply status is a power outage status, extract the multi-dimensional data factor indicators of each sub-module according to the real-time data, and respectively set the real-time multi-dimensional data factor values. Obtain the corresponding recommendation factors according to the real-time multi-dimensional factor values and the real-time weights; establish a time resource pool, and allocate the maximum working time of each sub-module to the time resource pool;

[0046] S200: Obtain the characteristic indicators of the power consumption end, select sub-modules according to the characteristic indicators of the power consumption end, the recommended factors of each sub-module, and the time resource pool, and form multiple power supply sequences.

[0047] S300: Calculate the total switching time of the sub-modules in each power supply sequence, and mark the power supply sequence with the minimum switching total time as the initial power supply sequence.

[0048] In some embodiments, the ATSE (Automatic Transfer Switching Equipment) is an electrical device used for automatic switching between the main power supply and the standby power supply to ensure power supply continuity; the UPS (Uninterruptible Power Supply) is a power supply system composed of battery energy storage, an inverter, and a control circuit, which provides temporary power when the main power supply is interrupted. A modular power supply group is set in the UPS power supply, which is a power supply unit composed of multiple independent sub-modules. Each sub-module can work independently or operate in cooperation. For each power consumption end, a corresponding preferred modular power supply group can be set. A sub-module refers to a power supply unit with independent power supply capabilities, including components such as a battery pack, an inverter, and a control circuit, and has functions such as voltage output, power regulation, and status monitoring, and is a modular power supply for power supply; the number of the power consumption ends is greater than 1.

[0049] In some embodiments, the input voltage, current, and frequency of the power consumption end are monitored in real time through a voltage sensor, a current sensor, and a PLC (Programmable Logic Controller). If the input voltage is lower than 85% of the rated value or the frequency deviation exceeds ±2 Hz and lasts for 10 ms, it is determined as a power supply interruption state.

[0050] In some embodiments, multi-dimensional data factor indicators are collected for each sub-module. The multi-dimensional data factor indicators include multiple factor indicators, and each factor indicator corresponds to a multi-dimensional data factor value and an initial weight. The initial weight is preset according to historical experimental data; the multi-dimensional data factor indicators include but are not limited to: voltage state, capacity margin, historical reliability, rated power, and working efficiency, etc.; the voltage state refers to the output voltage of each sub-module power supply and its fluctuation range; the capacity margin refers to the remaining power or available time of each sub-module power supply; the historical reliability refers to the historical failure rate, maintenance records, etc. of each sub-module power supply; the rated power refers to the maximum output power of each sub-module power supply; the working efficiency refers to the energy conversion efficiency of each sub-module power supply during operation.

[0051] In some embodiments, obtaining real-time weights based on real-time multi-dimensional data factor values and preset initial weights includes: pre-constructing a dynamic weight model and setting initial weights, obtaining multiple historical multi-dimensional data factor values corresponding to the initial weights, respectively obtaining the ratios of the real-time multi-dimensional data factor values to the historical multi-dimensional data factor values, adjusting the initial weights according to the ratios, and setting the adjusted initial weights as the real-time weights.

[0052] Construct a dynamic weight model, obtain the multi-dimensional data factors of each sub-module according to real-time data, and adjust the initial weights according to the multi-dimensional data factors to obtain real-time weights. For example, when the voltage fluctuation of a certain sub-module power supply is large, the weight of the voltage state can be appropriately increased; preferably, a pre-set adjustment strategy is used to perform weighted averaging on the multi-dimensional data factors and real-time weights in the real-time data to obtain corresponding recommendation factors.

[0053] For example, allocate initial weights (the sum of weights is 1) to each factor according to historical experimental data: voltage state: 0.25; capacity margin: 0.30; historical reliability: 0.20; rated power: 0.15; working efficiency: 0.10. Calculate the ratio of the real-time factor value to the historical reference value (such as the voltage fluctuation ratio is equal to the ratio of the voltage in the real-time multi-dimensional data factor value to the voltage in the historical multi-dimensional data factor value). If the ratio exceeds the threshold (such as greater than 1.2), adjust the weights according to the preset rules. When the voltage fluctuation ratio of a certain sub-module is greater than 1.5, the weight of its voltage state increases to 0.35, and other weights are reduced proportionally.

[0054] The weighted average method is used to calculate the recommendation factor of each sub-module. The calculation formula is as follows:

[0055]

[0056] where, RF is the recommendation factor; n is the total number of multi-dimensional data factor indicators; W i is the real-time weight of the i-th multi-dimensional data factor indicator; F i is the real-time multi-dimensional data factor value of the i-th multi-dimensional data factor indicator. Before calculation, all real-time multi-dimensional data factor values need to be normalized so that each multi-dimensional index is in the same dimension for easy data processing; n is the total number of multi-dimensional data factor indicators.

[0057] In some embodiments, establish a time resource pool, calculate the maximum working time of each sub-module according to the capacity margin and load power of each sub-module, allocate it to the time resource pool, store the maximum working time of each sub-module in the time resource pool, and arrange them in descending order.

[0058] In some embodiments, the power supply state of the power consumption end is monitored in real time through sensors or monitoring devices, and the characteristic indexes of the power consumption end are extracted. The characteristic indexes of the power consumption end include the power demand, voltage demand, and power consumption period of the power consumption end.

[0059] In some embodiments, calculate the total switching time of the sub-modules in each power supply sequence, and select the power supply sequence with the minimum total switching time for power supply. First, switching time monitoring needs to be carried out. The total switching time includes the ATSE action time, sub-module start-up delay, and path switching delay. The ATSE action time refers to the time from issuing the switching instruction to the contact closing; the sub-module start-up delay refers to the time from receiving the power supply instruction (starting) to the stable output (full power output) of the sub-module; the path switching delay refers to the switching time between different paths when generating multiple parallel power supply paths. Calculate the total switching time for each power supply sequence, and the calculation formula is as follows:

[0060]

[0061] Where, T total is the total switching time, T ai is the i-th ATSE action time, T si is the start-up delay of the i-th sub-module, T yi is the i-th path switching delay. When there is no path switching, the path switching delay can be 0.

[0062] Select the power supply sequence with the minimum total switching time from multiple power supply sequences to execute power supply. If the total switching times of multiple power supply sequences are the same, preferentially select the power supply sequence with the highest sum of recommendation factors.

[0063] The technical solutions in the embodiments of the present application at least have the following technical effects or advantages:

[0064] By monitoring the power supply state in real time and dynamically adjusting the recommendation factors of the sub-modules in the present application, it is possible to quickly respond to power supply interruptions, select the power supply sequence with the minimum total switching time as the optimal power supply sequence, improve power supply continuity, and achieve the effect of improving power supply efficiency; establish a time resource pool, and reasonably allocate the maximum working time according to the capacity margin of the sub-modules and the load power to ensure the efficient use of resources; based on multi-dimensional data factor indexes and dynamic weight adjustment, it can adapt to the needs of different power consumption ends and the state changes of the sub-modules, enhancing the flexibility and adaptability of the system.

[0065] Embodiment 2: In Embodiment 1, the optimal power supply sequence is selected by calculating the switching time between sub-modules, which further reduces the power supply time. However, different switching times correspond to different voltage fluctuations, affecting the switching efficiency. This embodiment makes further improvements on the basis of the above embodiment.

[0066] The method further includes: S400: Obtain the initial power supply order, calculate the optimal switching time for each sub-module according to the voltage matching mechanism; determine the actual charge amount of each sub-module according to the optimal switching time of each sub-module;

[0067] S410: Adjust the power supply time of the initial power supply order based on the optimal switching time and the actual charge amount to form an optimal power supply order.

[0068] The voltage matching mechanism is set as follows: Monitor the output voltage waveform and phase of each sub-module in real time to obtain voltage values and phase information; preset a voltage difference threshold and a phase difference threshold, and calculate the voltage difference and phase difference between any adjacent sub-modules at each time point according to the voltage values and phase information of each sub-module; select the time points corresponding to the voltage difference and phase difference that simultaneously satisfy the voltage difference threshold and the phase difference threshold, and use them as a preliminary candidate set of switching time points; obtain the candidate set of switching time points, form a fluctuation curve according to the time series, preliminarily divide time windows for the fluctuation curve, calculate the smoothness within each time window respectively, and select the time window with the highest smoothness as the candidate curve; evaluate the stability value of each time point in the candidate curve, and set the time point with the highest stability value as the optimal switching time. The optimal switching time refers to the optimal switching time point or the determined position. For example, when the optimal switching time is set to the 15th second after the power supply order starts, it specifically needs to be set according to the actual situation, and this application does not make specific requirements here.

[0069] In some embodiments, collect the output voltage waveform and phase information of each sub-module in real time, and ensure the time synchronization and accuracy of the data. For each pair of adjacent sub-modules, calculate the voltage difference and phase difference between any adjacent sub-modules. The voltage difference refers to the voltage difference value between adjacent sub-modules, and the phase difference is the phase angle difference between two waveforms. Since the phase angle is periodic (usually with a period of 360 degrees), the periodicity needs to be considered when calculating the phase difference. At the same time, the directionality of the phase difference is also very important, that is, which waveform leads or lags. For example, the phase angle of waveform A is φ A , the phase angle of waveform B is φ B , and the initial phase difference is φ A - φ B .

[0070] Preset a voltage difference threshold and a phase difference threshold to ensure that the selected switching time point can achieve a smooth transition of voltage and phase. Traverse all possible time points, calculate the voltage difference and phase difference at each time point, and select the time points that simultaneously satisfy the voltage difference and phase difference thresholds as a preliminary candidate set of switching time points.

[0071] Obtain a candidate set of switching time points. According to historical data or real-time monitored data, clean the data, remove outliers or noise, smooth the data, analyze the voltage fluctuation range of each sub-module, calculate the mean and standard deviation of the voltage of each sub-module. The mean represents the central tendency of the voltage, and the standard deviation represents the voltage fluctuation range. Preferably, calculate the fluctuation ranges at different time periods to obtain a more comprehensive fluctuation situation, and form a fluctuation curve according to the time series.

[0072] Smooth the fluctuation curve based on a smoothing method (such as moving average method or exponential smoothing method). Initially divide time windows for the processed fluctuation curve. The range of the time window needs to be preset according to the actual situation. Calculate the smoothness within each time window respectively. The smoothness is evaluated and calculated through indicators such as the standard deviation, variance, or mean square error of the curve. Select the time window with the highest smoothness as the candidate curve.

[0073] Evaluate the stability value of each time point in the candidate curve. The stability value is evaluated according to stability indicators, including three indicators: the stability of voltage difference and phase difference, system stability, and future trend stability. Obtain the corresponding numerical values for each indicator, preset the corresponding weights, and perform weighted summation to obtain the stability value; set the time point with the highest stability value as the optimal switching time. Specifically, for the stability of voltage difference and phase difference, calculate the average value and standard deviation of the voltage difference and phase difference within a period of time before and after each candidate time point, and select the time point with the average value close to the preset threshold and a smaller standard deviation; system stability is used to consider other stability factors of the system, such as current, temperature, etc. If the system is also stable in these aspects, the candidate time point is more advantageous; future trend prediction is to perform short-term prediction on the voltage difference and phase difference through appropriate prediction methods (such as exponential smoothing method, ARIMA model, etc.), and select the time point with relatively stable prediction results. If there are multiple candidate time points that meet the conditions, factors such as the convenience of actual operation and the load situation of the system can be further considered to determine the final optimal time point. This application does not make specific limitations here.

[0074] In this embodiment, based on the optimal switching time, adjust the switching time and charging time of the corresponding power supply order, further reduce the total switching time of the power supply order, and improve the power supply efficiency.

[0075] The technical solutions in the above embodiments of this application have at least the following technical effects or advantages:

[0076] By considering the voltage fluctuations corresponding to different switching times, combining the voltage matching mechanism and fluctuation curve analysis, this application selects the optimal switching time, further improves the switching efficiency, reduces the switching time, ensures the overall stability during the switching process, and improves the power supply efficiency.

[0077] Embodiment 3: In the above content, the selection of the power supply order is achieved through local optimization. However, when multiple power-consuming terminals share sub-modules, there are the same sub-modules among different power supply orders, resulting in conflicts in the switching timing and thus affecting the overall efficiency. This embodiment makes further improvements on the basis of the above.

[0078] The method further includes: S500: Detect the repeated sub-modules in different optimal power supply orders and mark them as the same sub-modules;

[0079] Collect the output voltage waveforms, phases, and optimal switching times of the sub-modules in all power supply orders in real time, and mark the optimal switching times of the same sub-modules in different power supply orders as phase analysis nodes;

[0080] Calculate the compensation difference at the phase analysis nodes. If the compensation difference is greater than the preset compensation threshold, calculate the adjusted switching time; taking the same sub-module as a node and the edge weight as the phase compensation cost, construct a directed graph and identify the phase coordination relationship across power supply orders;

[0081] S510: Establish a numerical evaluation model for the switching time, obtain a scoring factor, and select the adjustment scheme with the largest scoring factor for adjustment and optimization.

[0082] The numerical evaluation model for the switching time is based on the phase coordination relationship, obtains the index values of three indicators: switching efficiency, subsequent influence degree, and stability coefficient, and comprehensively calculates the scoring factor according to the index values of the three indicators; the calculation formula is as follows:

[0083]

[0084] Among them, Score is the scoring factor, E is the switching efficiency, I is the subsequent influence degree, S is the stability coefficient, α, β, and γ are the corresponding weight coefficients respectively, α + β + γ = 1, by default α = 0.5, β = 0.3, γ = 0.2, and specific pre-adjustment needs to be carried out according to the actual situation.

[0085] In some embodiments, the calculation method of the compensation difference is: according to the time interval between different phase analysis nodes, calculate the proportion of the time interval in the power supply cycle respectively, and convert it into the corresponding angle. The calculation formula is as follows:

[0086]

[0087] Among them, is the compensation difference, t i is the switching time of the i-th power supply order, t jis the switching opportunity of the j-th power supply sequence, and T is the power supply period, which is preset according to the load fluctuation period of the power consumption end and defaults to the power frequency period of 20 ms. For example, when the sub-module A needs to switch at t = 5 ms in the power supply sequence 1 and at t = 15 ms in the power supply sequence 2, and T = 20 ms, If the compensation threshold is set to 30°, then adjust the switching of the power supply sequence 2 to t = 5 ms or t = 25 ms( ), that is, in the same phase. When selecting the object to be adjusted, preferentially select the best switching opportunity that is closest to the adjusted switching opportunity for adjustment, reduce the adjustment amplitude, and avoid having too much impact on the subsequent switching opportunities.

[0088] In some embodiments, taking the same sub-module as a node and the edge weight as the phase compensation cost, a directed graph is constructed, and the phase coordination relationship across power supply sequences is identified. The phase coordination relationship refers to the mutual association and influence of the same sub-module (i.e., the sub-module that appears repeatedly in different power supply sequences) in terms of switching opportunities in different power supply sequences. Due to different power supply sequences, the same sub-module may need to switch at different time points, and the differences in these switching opportunities may lead to phase deviations, thereby affecting the overall performance and stability of the system. Therefore, it is necessary to analyze and adjust these switching opportunities to ensure the coordinated operation of the sub-module in different power supply sequences. A directed graph is a graph structure where nodes represent entities (in this case, sub-modules), and edges represent the relationships between nodes (in this case, the phase compensation cost). The edges are directed, indicating the relationship or influence from one node to another. In a directed graph, the strength or cost of the relationship can be represented by the weight of the edge.

[0089] Define each sub-module as a node. If a sub-module appears repeatedly in different power supply sequences, they are regarded as the same node. For each pair of the same sub-modules that appear in different power supply sequences, calculate the compensation difference between their best switching opportunities in different power supply sequences. Take the compensation difference as the edge weight, representing the phase compensation cost. The larger the compensation difference, the higher the compensation cost. Use graph theory data structures (such as adjacency matrices or adjacency lists) to represent the directed graph. For each pair of the same sub-modules, if there is a difference in switching opportunities in different power supply sequences, add a directed edge in the graph. The starting point and ending point of the edge respectively correspond to the sub-module nodes in two power supply sequences, and the weight of the edge is the compensation difference. In the directed graph, the phase coordination relationship across power supply sequences is identified through the existence and weight of the edges. It is possible to identify which sub-modules have phase coordination problems in different power supply sequences and the severity of these problems by analyzing the topological structure of the graph.

[0090] Establish a switching timing numerical evaluation model, calculate the scoring factors, select the adjustment plan with the largest scoring factor for adjustment and optimization, determine the switching efficiency according to the total switching time of the power supply sequence corresponding to each switching timing that needs to be adjusted, and analyze the switching process of each sub-module in different power supply sequences for each sub-module. Calculate parameters such as energy loss and response time during the switching process, and use a predefined evaluation function to calculate the switching efficiency index value based on these parameters.

[0091] Obtain the subsequent influence degree according to the delay ratio of the best switching timing of the subsequent sub-module with respect to the switching timing; simulate the system state after the sub-module switches, analyze the influence of the switching on the working state and system performance of the sub-module in the subsequent power supply sequence, etc., and use a predefined evaluation function to calculate the subsequent influence degree index value based on the influence degree.

[0092] Perform a stability score to obtain the stability coefficient according to the voltage difference, compensation difference, and phase coordination relationship of the switching timing; analyze the dynamic response of the system after the sub-module switches, calculate parameters such as the oscillation frequency and attenuation rate of the system, and use a predefined evaluation function to calculate the stability coefficient index value based on these parameters.

[0093] Calculate the scoring factors using a formula according to the predefined weight coefficients. Select the adjustment plan with the largest scoring factor for adjustment and optimization; in this embodiment, through phase coordination analysis, numerical evaluation, and dynamic time adjustment, global optimization across power supply sequences is achieved.

[0094] The technical solutions in the embodiments of the present application described above have at least the following technical effects or advantages:

[0095] The present application solves the problem of switching timing conflicts between different power supply sequences when multiple power-consuming terminals share sub-modules by marking the same sub-module, calculating the compensation difference, and adjusting the switching timing; through phase coordination analysis and numerical evaluation, global optimization across power supply sequences is achieved, improving the overall efficiency and stability of the system; when selecting the adjustment object, the best switching timing closest to the adjusted switching timing is preferentially selected for adjustment, reducing the adjustment range and the impact on subsequent switching timings.

[0096] Embodiment 4: This embodiment makes further improvements on the basis of the above content.

[0097] In the scenario of sharing power supply sub-modules at a multi-purpose power end, due to different power supply sequences and the repeated use of sub-modules, conflicts in the switching timing may affect the overall efficiency. The above embodiments achieve global optimization across power supply sequences through phase coordination analysis and numerical evaluation. To further improve the flexibility and stability of the system, this embodiment proposes a hierarchical switching control strategy. This strategy divides the power supply sub-modules and power ends into different levels according to factors such as importance, energy efficiency requirements, and flexibility, ensuring the priority guarantee of key power supply functions, and at the same time achieving overall system optimization through the flexible adjustment of low-level modules.

[0098] The method further includes: S511: Classify the sub-modules according to the factor index set of the sub-modules, and classify the power ends according to the factor index set of the power ends, respectively into high-level, medium-level, and low-level; calculate the module level score of the same sub-module and the power consumption level score of the corresponding power end.

[0099] S512: Obtain a level adjustment coefficient based on the module level score and the power consumption level score, adjust the scoring factor based on the level adjustment coefficient, and select the adjustment scheme corresponding to the largest adjusted scoring factor for adjustment and optimization.

[0100] In some embodiments, the factor index set of the sub-module should comprehensively consider factors such as its importance, energy efficiency, reliability, and flexibility in the power supply system. Specific indicators include but are not limited to: Importance index: Reflects the key degree of the sub-module in the power supply system, such as whether it is part of the core power supply path; Energy efficiency ratio: The efficiency of the sub-module when converting electrical energy; Reliability score: The reliability evaluated based on historical failure rates and maintenance records; Flexibility index: The ability of the sub-module to adjust the switching timing, such as fast response speed and large adjustment range. Set a quantitative standard or scoring system for each indicator, and score each sub-module according to the above indicators.

[0101] The factor index set of the power end should consider its load type, requirements for power supply stability, energy efficiency requirements, and importance in the economy or system. Specific indicators include but are not limited to: Importance of load type: Such as critical loads (servers, medical equipment) and non-critical loads (lighting, air conditioning); Requirements for power supply stability: Tolerance for voltage fluctuations and interruptions; Energy efficiency requirements: Energy efficiency standards or targets of the power end; System importance: The value of the power end in the economy or system. Set a quantitative standard or scoring system for each indicator, and score each power end according to the above indicators.

[0102] Score according to the factor index set of the sub-module, and obtain the module level score through weighted average; score according to the factor index set of the power end, and obtain the power consumption level score through weighted average. Preset the weights of each indicator to reflect their relative importance, and calculate the level score using the weighted average method according to the indicator values and the corresponding weight values.

[0103] The purpose of adjusting the scoring factor is to give priority to the needs of high-level sub-modules and the power consumption end when optimizing the switching timing, set the calculation formula of the basic scoring factor, introduce a level adjustment coefficient, give a positive bonus to high-level sub-modules and the power consumption end, and give a negative or smaller bonus to low-level ones; the adjusted scoring factor formula is: Adjusted scoring factor = Basic scoring factor × Level adjustment coefficient. The level adjustment coefficient is obtained based on a linear or non-linear function. For example, the adjustment coefficients of high-level sub-modules and the power consumption end are greater than 1, and those of low-level ones are less than 1. Specific adjustments need to be made according to the actual situation. Using linear or non-linear functions belongs to well-known technologies, and this application will not elaborate too much here.

[0104] The technical solutions in the embodiments of the present application at least have the following technical effects or advantages:

[0105] Through the hierarchical switching control strategy, this application ensures the priority guarantee of key power supply functions, and at the same time realizes the overall optimization of the system through the flexible adjustment of low-level modules; by adjusting the scoring factor based on the levels of sub-modules and the power consumption end, the optimization process becomes more refined and targeted; by setting quantitative standards and a scoring system, and introducing a level adjustment coefficient, the system can better adapt to different application scenarios and demand changes.

[0106] Embodiment 5: As Figure 2 shown, this embodiment also provides an uninterruptible power supply system based on ATSE and UPS, which is applied to the above-mentioned uninterruptible power supply method based on ATSE and UPS. The system includes:

[0107] A state monitoring and data analysis module, which is used to monitor the power supply state of the power consumption end in real time, extract multi-dimensional data factor indicators of each sub-module, and calculate the real-time multi-dimensional data factor values; pre-construct a dynamic weight model, set the initial weight, and adjust the initial weight to the real-time weight according to the real-time multi-dimensional data factor values; calculate the recommendation factor according to the real-time multi-dimensional data factor values and the real-time weight; establish a time resource pool and allocate the maximum working time of each sub-module.

[0108] The state monitoring and data analysis module provides data support and recommendation factors for the power supply order selection module, and interacts with the weight adjustment module to obtain the real-time weight.

[0109] A power supply order generation module, which is used to obtain the power consumption end characteristic indicators, select sub-modules to form multiple power supply orders according to the power consumption end characteristic indicators, the recommendation factors of each sub-module, and the time resource pool; calculate the total switching time of the sub-modules in each power supply order, and select the power supply order with the minimum total switching time as the initial power supply order.

[0110] The power supply sequence generation module depends on the data and recommendation factors provided by the state monitoring and data analysis module, and provides an initial power supply sequence for the optimal switching time calculation module.

[0111] The optimal switching time calculation module is used to, according to the voltage matching mechanism, monitor the output voltage waveforms and phases of each sub-module in real time, calculate the voltage difference and phase difference, select the time points that meet the voltage difference threshold and phase difference threshold as the initial candidate set of switching time points, evaluate the time points in the candidate curve, and determine the optimal switching time; adjust the initial power supply sequence according to the optimal switching time and the actual charge amount to form the optimal power supply sequence.

[0112] The optimal switching time calculation module receives the initial power supply sequence provided by the power supply sequence selection module, and provides the optimal power supply sequence and switching time for the power supply time adjustment and optimization module.

[0113] The power supply adjustment and optimization module is used to detect the sub-modules that are repeated in different optimal power supply sequences and mark them as the same sub-modules, collect the output voltage waveforms, phases and optimal switching times of the sub-modules in all power supply sequences in real time, and perform phase analysis; establish a numerical evaluation model for the switching time, comprehensively calculate the switching efficiency, subsequent influence degree and stability coefficient to obtain a scoring factor, and select the adjustment plan with the largest scoring factor for adjustment and optimization. The power supply adjustment and optimization module depends on the optimal power supply sequence and switching time provided by the optimal switching time calculation module, and interacts with the grading and scoring adjustment module to consider the influence of the grading of the module and the power consumption end on the scoring factor.

[0114] The grading module is used to grade the sub-modules according to the factor index set of the sub-modules, and grade the power consumption end according to the factor index set of the power consumption end.

[0115] The grading module provides the grading result for the power supply time adjustment and optimization module. The power supply time adjustment and optimization module obtains the module grade score and the power consumption grade score based on the divided grades, and then obtains the grade adjustment coefficient. The scoring factor is adjusted based on the grade adjustment coefficient to obtain the adjusted scoring factor, and the adjustment plan is selected based on the adjusted scoring factor for adjustment and optimization.

[0116] The above is only the preferred embodiment of the present invention and is not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An uninterruptible power supply method based on an ATSE and a UPS, characterized in that, The method includes: S100: Obtain the power supply status of the power consumption end. If the power supply status is a power interruption status, extract the multi-dimensional data factor indicators of each sub-module according to real-time data, and set the real-time multi-dimensional data factor values respectively. Obtain the corresponding recommendation factors according to the real-time multi-dimensional factor values and real-time weights; establish a time resource pool, and allocate the maximum working time of each sub-module to the time resource pool; S200: Obtain the characteristic indicators of the power consumption end, and select sub-modules according to the characteristic indicators of the power consumption end, the recommendation factors of each sub-module, and the time resource pool to form multiple power supply sequences; S300: Calculate the total switching time of the sub-modules in each power supply sequence, and mark the power supply sequence with the minimum switching total time as the initial power supply sequence.

2. The uninterruptible power supply method based on ATSE and UPS according to claim 1, characterized in that, The method further includes: S400: Obtain the initial power supply sequence, and calculate the optimal switching time of each sub-module according to the voltage matching mechanism; determine the actual charge of each sub-module according to the optimal switching time of each sub-module; S410: Adjust the power supply time of the initial power supply sequence based on the optimal switching time and the actual charge to form the optimal power supply sequence.

3. The uninterruptible power supply method based on ATSE and UPS according to claim 2, wherein The voltage matching mechanism is set as: Monitor the output voltage waveform and phase of each sub-module in real time to obtain voltage values and phase information; Preset a voltage difference threshold and a phase difference threshold, and calculate the voltage difference and phase difference between any adjacent sub-modules at each time point according to the voltage values and phase information of each sub-module; Select the time points corresponding to the voltage difference and phase difference that simultaneously satisfy the voltage difference threshold and the phase difference threshold, and use them as the preliminary switching time point candidate set; Obtain the switching time point candidate set, form a fluctuation curve according to the time series, preliminarily divide the time window of the fluctuation curve, calculate the smoothness within each time window respectively, and select the time window with the highest smoothness as the candidate curve; Evaluate the stability value of each time point in the candidate curve, and set the time point with the highest stability value as the optimal switching time.

4. The uninterruptible power supply method based on ATSE and UPS according to claim 3, characterized in that The method further includes: S500: Detect the sub-modules repeated in different optimal power supply sequences and mark them as the same sub-modules; Collect the output voltage waveforms, phases, and optimal switching times of the sub-modules in all power supply sequences in real time, and mark the optimal switching times of the same sub-modules in different power supply sequences as phase analysis nodes; Calculate the compensation difference at the phase analysis node. If the compensation difference is greater than the preset compensation threshold, calculate the adjusted switching time; Construct a directed graph with the same sub-module as the node and the edge weight as the phase compensation cost, and identify the phase coordination relationship across power supply sequences; S510: Establish a switching time numerical evaluation model to obtain a scoring factor, and select the adjustment scheme with the largest scoring factor for adjustment and optimization.

5. The uninterruptible power supply method based on ATSE and UPS according to claim 4, characterized in that, The switching time numerical evaluation model is based on the phase coordination relationship to obtain the index values of three indicators: switching efficiency, subsequent influence degree, and stability coefficient, and comprehensively calculate the scoring factor according to the index values of the three indicators; The calculation formula is as follows: Among them, Score is the scoring factor, E is the switching efficiency, I is the subsequent influence degree, S is the stability coefficient, and α, β, and γ are the corresponding preset weight coefficients respectively.

6. The uninterruptible power supply method based on ATSE and UPS according to claim 1, wherein Obtain the real-time weight according to the real-time multi-dimensional data factor values and the preset initial weights, including: Pre-construct a dynamic weight model and set the initial weights, obtain multiple historical multi-dimensional data factor values corresponding to the initial weights, and respectively obtain the ratios of the real-time multi-dimensional data factor values to the historical multi-dimensional data factor values. Adjust the initial weights according to the ratios, and set the adjusted initial weights as the real-time weights.

7. The uninterruptible power supply method based on ATSE and UPS according to claim 1, characterized in that The multi-dimensional data factor indicators include voltage status, capacity margin, historical reliability, rated power, and working efficiency; the power consumption end characteristic indicators include the power demand, voltage demand, and power consumption period of the power consumption end.

8. The uninterruptible power supply method based on ATSE and UPS according to claim 1, characterized in that, The total switching time includes the ATSE action time, sub-module start-up delay, and path switching delay. The ATSE action time refers to the time from issuing the switching instruction to the contact closing; the sub-module start-up delay refers to the time from the sub-module receiving the power supply instruction to stable output; the path switching delay refers to the switching time between different paths in multiple parallel power supply paths.

9. The uninterruptible power supply method based on ATSE and UPS according to claim 4, wherein The method further includes: S511: Classify the sub-modules according to the factor index set of the sub-modules, and classify the power consumption end according to the factor index set of the power consumption end, and divide them into high level, medium level, and low level respectively; calculate the module level score value of the same sub-module and the power consumption level score value of the corresponding power consumption end. S512: Obtain the level adjustment coefficient based on the module level score value and the power consumption level score value, adjust the scoring factor based on the level adjustment coefficient, and select the adjustment scheme corresponding to the largest adjusted scoring factor for adjustment and optimization.

10. An uninterruptible power supply system based on an ATSE and a UPS, which is applied to the uninterruptible power supply method based on an ATSE and a UPS according to any one of claims 1 to 9, is characterized in that, The system includes: A status monitoring and data analysis module, which is used to monitor the power supply status of the power consumption end in real time, extract the multi-dimensional data factor indicators of each sub-module, and calculate the real-time multi-dimensional data factor values; pre-construct a dynamic weight model, set the initial weights, and adjust the initial weights to real-time weights according to the real-time multi-dimensional data factor values; calculate the recommendation factor according to the real-time multi-dimensional data factor values and the real-time weights; establish a time resource pool and allocate the maximum working time of each sub-module. A power supply order generation module, which is used to obtain the power consumption end characteristic indicators, select sub-modules to form multiple power supply orders according to the power consumption end characteristic indicators, the recommendation factors of each sub-module, and the time resource pool; calculate the total switching time of the sub-modules in each power supply order, and select the power supply order with the minimum total switching time as the initial power supply order. An optimal switching timing calculation module, which is used to calculate the voltage difference and phase difference by monitoring the output voltage waveform and phase of each sub-module in real time according to the voltage matching mechanism, select the time points that meet the voltage difference threshold and phase difference threshold as the preliminary switching time point candidate set, evaluate the time points in the candidate curve, and determine the optimal switching timing; adjust the initial power supply order according to the optimal switching timing and the actual charge amount to form the optimal power supply order. The power supply adjustment and optimization module is used to detect the repeated sub-modules in different optimal power supply sequences, mark them as the same sub-module, collect the output voltage waveforms, phases and optimal switching times of the sub-modules in all power supply sequences in real time, and conduct phase analysis; establish a numerical evaluation model for switching times, comprehensively calculate the switching efficiency, subsequent influence degree and stability coefficient, obtain a scoring factor, and select the adjustment scheme with the largest scoring factor for adjustment and optimization; The grading module is used to grade the sub-modules according to the factor index set of the sub-modules, and grade the power consumption end according to the factor index set of the power consumption end.

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