Multi-directional topology ac-dc intelligent conversion emergency power supply system and working method thereof

Abstract

The multi-directional topology AC-DC intelligent conversion emergency power supply system and its working method, comprising: a redundant design module configures redundant solid-state relays in the solid-state relay matrix of each emergency power supply terminal according to the historical use frequency and historical failure frequency of various energy load connection modes; a data acquisition module acquires the energy state characteristics, load demand characteristics and solid-state relay state data of each emergency power supply terminal in real time under the set operation constraints of energy and load; an energy path decision module is used to generate the energy transmission optimal path of each emergency power supply terminal to realize various energy load connection modes, and generate the action instruction of the solid-state relay associated with the energy transmission optimal path; a composite control module is used to determine the load mutation type according to the operation monitoring data of each emergency power supply terminal, and if the load mutation type is non-solid-state relay failure, voltage compensation is performed, which significantly improves the response speed and control accuracy of the emergency power supply.

Description

Technical Field

[0001] This invention relates to the field of power management technology, specifically to an AC / DC intelligent conversion emergency power supply system based on a multi-directional topology and its operating method. Background Technology

[0002] Traditional emergency power systems exhibit numerous problems when facing complex and ever-changing working scenarios. Firstly, they are inadequate in energy status monitoring and utilization. Common emergency power supplies often rely on a single energy source, such as batteries. When the battery is depleted or not recharged in time, continuous power supply is impossible. Even with renewable energy supplements like photovoltaics, it's difficult to accurately respond to rapid changes in energy status. In practical applications, complex weather conditions cause photovoltaic power to fluctuate drastically, resulting in a sudden drop in output power. Traditional emergency power systems cannot flexibly adjust energy paths in a short time or switch to a combined power supply mode promptly, severely impacting load power supply and failing to meet the reliability requirements of emergency power. Secondly, different load types have varying electrical characteristics. When the load suddenly increases or changes, traditional emergency power systems struggle to adapt quickly. Inductive loads generate inrush currents when starting, putting immense pressure on the power system. Converters in traditional emergency power systems often cannot withstand such surges, easily leading to current overload and voltage drops, affecting the normal operation of the load. Moreover, traditional emergency power supply systems rely on a single detection method, such as monitoring only the rate of change of current to determine load changes. This is prone to misjudgment, cannot accurately identify the type of load change, and is difficult to achieve targeted control. As a result, the response speed and control accuracy of the entire emergency power supply system cannot meet the actual needs, which seriously affects the stability and reliability of emergency power supply. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a multi-directional topology AC / DC intelligent conversion emergency power supply system and its operating method. This system enables real-time monitoring of the operation of each emergency power supply terminal, and adopts different response mechanisms and pre-compensates the voltage for each terminal based on the monitoring results, significantly improving the response speed and control accuracy of the emergency power supply.

[0004] The present invention adopts the following technical solution.

[0005] This invention proposes a multi-directional topology AC / DC intelligent conversion emergency power supply system, deployed in the cloud and communicating in a distributed manner with multiple emergency power supply terminals. Each emergency power supply terminal includes a solid-state relay matrix; comprising: The redundancy design module is used to configure redundant solid-state relays in the solid-state relay matrix of each emergency power terminal based on the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power terminal. The data acquisition module is used to collect the energy status characteristics, load demand characteristics, and solid-state relay status data of each emergency power terminal in real time under the set operating constraints of energy and load of each emergency power terminal. The energy path decision module is used to generate the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods by utilizing the energy status characteristics and load demand characteristics of each emergency power terminal, and to generate the action command of the solid-state relay associated with the optimal energy transmission path. The composite control module is used to determine the type of load mutation based on the operation monitoring data of each emergency power terminal. If the load mutation type is a solid-state relay fault, the faulty solid-state relay is disconnected. If there is a redundant solid-state relay for the faulty solid-state relay, the redundant solid-state relay is closed. If the load mutation type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud. The voltage compensation amount at the current moment is monitored at subsequent moments. If a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval starting from the subsequent moment, a predicted compensation voltage amount is generated based on the voltage compensation amount at the current moment and the fixed time interval, and uploaded to the cloud.

[0006] The redundant design module connects to the expansion terminals of the solid-state relay matrix of each emergency power supply terminal; The data acquisition module connects to the energy-side port, load-side port, and solid-state relay matrix of each emergency power terminal; Both the energy path decision module and the composite control module are connected to the drive end of the solid-state relay matrix of each emergency power supply terminal. The redundant design module transmits signals to the data acquisition module, the data acquisition module transmits signals to the energy path decision module and the composite control module, and the energy path decision module transmits signals to the composite control module; the composite control module interacts with the cloud for data exchange.

[0007] This invention also proposes a working method for a multi-directional topology AC / DC intelligent conversion emergency power supply system, including: Obtain the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power terminal, and configure redundant solid-state relays in the solid-state relay matrix of each emergency power terminal. Under the set operating constraints of energy and load for each emergency power terminal, the energy status characteristics, load demand characteristics and solid-state relay status data of each emergency power terminal are collected in real time. By utilizing the energy status characteristics and load demand characteristics of each emergency power terminal, the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods is generated, as well as the action command of the solid-state relay associated with the optimal energy transmission path is generated. The type of load mutation is determined based on the operation monitoring data of each emergency power supply terminal. If the load mutation type is a solid-state relay fault, the faulty solid-state relay is disconnected. If there is a redundant solid-state relay for the faulty solid-state relay, the redundant solid-state relay is closed. If the load mutation type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud. The voltage compensation amount at the current moment is monitored at subsequent moments. If, starting from subsequent moments, a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval, a predicted compensation voltage amount is generated based on the voltage compensation amount at the current moment and the fixed time interval, and uploaded to the cloud.

[0008] In a solid-state relay matrix, the energy load connection method associated with each solid-state relay is determined based on the energy type connected to the input terminal and the load type connected to the output terminal. The fuzzy comprehensive evaluation method is adopted to determine the importance level of various energy load connection methods based on their historical usage frequency and historical failure frequency, and then the importance level of the energy load connection method is mapped to the importance level of the associated solid-state relay. The importance level of various energy load connection methods is compared with a preset threshold, and redundant solid-state relays are configured for the solid-state relays associated with energy load connection methods whose importance level is greater than the preset threshold.

[0009] Build an online user interface, through which users can input operating constraints for energy and load; The energy input status, load demand status, and device status of the emergency power supply terminal's energy port, load port, and solid-state relay matrix are monitored respectively. Under the set operating constraints of energy and load, energy status characteristics, load demand characteristics, and solid-state relay status data are acquired, and the acquisition time of each characteristic is marked.

[0010] Multiple energy transmission paths are preset, and the importance level of the energy load connection method corresponding to each energy transmission path is marked; Each energy transport path is encoded with chromosomes and the population is initialized to generate an initial population and construct a fitness function. Based on the fitness function, a multi-objective genetic algorithm is used to determine the optimal energy transfer path under the constraints of energy and load operation.

[0011]

[0012] In the formula, For the fitness function, Indicates energy priority indicators, This represents the load demand matching index. Indicators representing the degree of energy state matching, Indicators representing importance levels This indicates the health indicators of a solid-state relay. , , This represents the weighting coefficients determined using the entropy weighting method. This is the health penalty factor for solid-state relays when they are redundantly configured. =1, when the solid-state relay is not redundantly configured. It is an integer greater than 1.

[0013] The energy priority index for mains power is 4, for photovoltaic power is 3, for energy storage battery packs is 2, and for backup generators is 1. If the solid-state relays in the path do not meet the load demand characteristics of the load, the load demand matching index of the path is 0; if the solid-state relays in the path meet the load demand characteristics of the load, the load demand matching index of the path is 1. Extract various operating parameters of energy from the path where the load demand matching degree index is 1. When the operating parameters meet the operating constraints of energy, the parameter compliance degree q=1. When the operating parameters do not meet the operating constraints of energy, the parameter compliance degree q=0. The sum of all parameter compliance degrees q is used as the energy state matching degree index. If there are multiple paths that meet the load demand characteristics and energy status characteristics, the highest importance level of the energy load connection method implemented by each energy transmission path is extracted as the importance level index. The importance level index value is 4 for special importance, 3 for first importance, 2 for second importance, and 1 for temporary importance.

[0014] The weighted sum of operating temperature health, on-state voltage drop health, and switching life health is used as the health index of solid-state relays;

[0015] In the formula, For working temperature health, , , These are the maximum, initial, and actual operating temperatures of the solid-state relay, respectively.

[0016] In the formula, For the health status of the on-state pressure drop, , , These are the maximum, allowable, and actual on-state voltage drop values ​​for the solid-state relay, respectively.

[0017] In the formula, For switch lifespan health, , These are the actual and design values ​​for the number of switching operations of the solid-state relay, respectively.

[0018] In the formula, For the health indicators of solid-state relays, , , These are the weighting coefficients.

[0019] A preset sliding window is used to calculate the voltage deviation rate at the current moment by utilizing the load demand characteristics within several sliding windows. and rate of change of current As shown below:

[0020]

[0021] In the formula, For a moment voltage value, The average voltage. For a moment The current value, The duration of the sliding window; Preset voltage deviation rate threshold and current change rate threshold. If the current change rate at the current moment is greater than the current change rate threshold, then perform multi-dimensional feature fusion judgment. A fault reference table is constructed, which includes different current change rates and multidimensional features corresponding to load mutation types. Feature extraction is performed on the current solid-state relay status data to determine multidimensional features. Based on the current current change rate, multidimensional features, and fault reference table, the load mutation type is determined.

[0022] If the load change type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transfer path, and the voltage compensation amount at the current moment is uploaded to the cloud; the cloud sends an instruction to the corresponding controller to compensate for the phase difference between the load voltage and current based on the voltage compensation amount. The voltage compensation at the current moment satisfies the following relationship: ,

[0023] In the formula, For a moment Voltage compensation amount, , These are the power supply internal resistance and line inductance in the equivalent circuit, respectively. For a moment The change in current, This is the steady-state current.

[0024] The present invention is also a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0025] The present invention is also a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0026] The beneficial effects of this invention are that, compared with the prior art, it at least includes the following: This invention considers that the energy state (such as photovoltaic power fluctuations, energy storage SOC decline) and load type (such as sudden load increase / switching) will change in real time, and proposes a module and method for continuously updating the energy transmission path through closed-loop feedback. By utilizing the flexibility of multi-directional topology, a cycle of sensing parameters → rule decision → topology execution → dynamic optimization is realized. Combined with the adaptability of energy state and load type, the system efficiency and energy utilization rate are maximized while ensuring the reliability of emergency power supply.

[0027] The composite control module utilizes a layered control approach of prediction, suppression, and fallback. It detects load surges by first assessing current changes and immediately triggers feedforward response control to compensate for voltage changes in advance, suppressing voltage fluctuations at their source. Simultaneously, voltage fluctuation detection serves as a fallback. If the load surge is too strong (e.g., a short circuit) or the feedforward control fails to completely offset the disturbance, causing the voltage deviation rate to exceed a threshold, a more forceful rapid response mechanism (switching solid-state relays) is triggered to ensure the load does not lose power or become damaged due to continuous voltage anomalies. Furthermore, during current change rate detection, multi-feature fusion is used to avoid misjudgments based on a single current change rate. Through causal correlation and timing coordination, a closed-loop control system is formed from disturbance occurrence to output stability, improving both response speed and control accuracy. This is the core guarantee for the speed and reliability of emergency power supply systems. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the structure of the multi-directional topology AC / DC intelligent conversion emergency power supply system proposed in this invention; Figure 2This is a flowchart of the working method of the multi-directional topology AC / DC intelligent conversion emergency power supply system proposed in this invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0030] This invention proposes a multi-directional topology AC / DC intelligent conversion emergency power supply system, deployed in the cloud and communicating in a distributed manner with multiple emergency power supply terminals, each of which includes a solid-state relay matrix; such as Figure 1 As shown, the system includes: The system comprises a redundancy design module, a data acquisition module, an energy path decision module, and a composite control module. The redundancy design module connects to the extension terminals of the solid-state relay matrices at each emergency power terminal. The data acquisition module connects to the energy-side ports, load-side ports, and solid-state relay matrices at each emergency power terminal. The energy path decision module and the composite control module both connect to the drive terminals of the solid-state relay matrices at each emergency power terminal. Signals from the redundancy design module are transmitted to the data acquisition module, which in turn transmits signals to the energy path decision module and the composite control module. The composite control module interacts with the cloud for data exchange.

[0031] The redundancy design module is used to configure redundant solid-state relays in the solid-state relay matrix of each emergency power terminal based on the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power terminal. The data acquisition module is used to collect the energy status characteristics, load demand characteristics, and solid-state relay status data of each emergency power terminal in real time under the set operating constraints of energy and load of each emergency power terminal. The energy path decision module is used to generate the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods by utilizing the energy status characteristics and load demand characteristics of each emergency power terminal, and to generate the action command of the solid-state relay associated with the optimal energy transmission path. The composite control module is used to determine the type of load mutation based on the operation monitoring data of each emergency power terminal. If the load mutation type is a solid-state relay fault, the faulty solid-state relay is disconnected. If there is a redundant solid-state relay for the faulty solid-state relay, the redundant solid-state relay is closed. If the load mutation type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud. The voltage compensation amount at the current moment is monitored at subsequent moments. If a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval starting from the subsequent moment, a predicted compensation voltage amount is generated based on the voltage compensation amount at the current moment and the fixed time interval, and uploaded to the cloud.

[0032] This invention also proposes a working method for an AC / DC intelligent conversion emergency power supply system based on a multi-directional topology, such as... Figure 2 As shown, it includes: Step 1: Obtain the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power supply terminal, and configure redundant solid-state relays in the solid-state relay matrix of each emergency power supply terminal.

[0033] Specifically, step 1 includes: Step 1.1: In the solid-state relay matrix, determine the energy load connection method associated with each solid-state relay based on the energy type connected to the input terminal and the load type connected to the output terminal. In this embodiment, the input terminals of the solid-state relay matrix are connected to different energy ports of the emergency power terminal, including but not limited to: photovoltaic port, energy storage port, mains power port, and backup generator port; the output terminals of the solid-state relay matrix are connected to different load ports of the emergency power terminal, including but not limited to: AC load port and DC load port; by controlling the on and off states of each solid-state relay in the matrix, flexible connections between multiple energy inputs and multiple load outputs can be achieved, forming complex energy transmission paths; a 4×4 solid-state relay matrix can theoretically achieve 16 different energy-load connection methods; Step 1.2: Using the fuzzy comprehensive evaluation method, the importance level of each energy load connection method is determined based on the historical usage frequency and historical failure frequency of each energy load connection method, and the importance level of the energy load connection method is mapped to the importance level of the associated solid-state relay. Specifically, step 1.2 includes: Step 1.2.1: Obtain the historical usage frequency and historical failure frequency of various energy load connection methods from the historical emergency data of the emergency power supply terminal as evaluation indicators, and set the importance level of the energy load connection methods. In the embodiments, the importance levels include: top level, first level, second level, and temporary; Step 1.2.2: Perform fuzzy evaluation on each evaluation index, and give the membership degree of various energy load connection methods to the importance level, forming a membership degree matrix. ; In this embodiment, the membership degree is normalized for ease of use; Step 1.2.3: Determine the weight of each evaluation index in various energy load connection methods, and construct a weight matrix for the evaluation indexes. ; In the embodiments, the weights are determined using the analytic hierarchy process (AHP) or the entropy weight method. Step 1.2.4: The weight matrix and membership matrix are fused using the following relationship to obtain the fuzzy comprehensive evaluation matrix:

[0034] in, The fuzzy comprehensive evaluation matrix of the evaluation indicators. The weight matrix for the evaluation indicators, For the membership matrix, "This indicates that the elements at corresponding positions in the weight matrix and membership matrix of the evaluation index are multiplied together." and These are the control parameters used to balance the weight matrix and the membership matrix, respectively. Step 1.2.5: Based on the fuzzy comprehensive evaluation matrix, the importance level corresponding to the maximum membership degree is used as the importance level of various energy load connection methods; Step 1.3: Compare the importance level of various energy load connection methods with the preset threshold, and configure redundant solid-state relays for the solid-state relays associated with energy load connection methods whose importance level is greater than the preset threshold. In this embodiment, the preset threshold is level one.

[0035] Step 2: Under the set operating constraints of energy and load for each emergency power terminal, collect the energy status characteristics, load demand characteristics, and solid-state relay status data of each emergency power terminal in real time.

[0036] Specifically, step 2 includes: Step 2.1: Construct an online user interface, through which users input operating constraints for energy and load. Specifically, the operating constraints of energy and load include, but are not limited to: energy input type, energy storage charge and discharge cutoff threshold, photovoltaic maximum power point (MPPT), generator continuous operating time, and load power, current, and voltage limit ranges. In this embodiment, the energy input types include, but are not limited to: photovoltaic, energy storage battery pack, backup generator, and mains power; the charge and discharge cutoff thresholds for energy storage include, but are not limited to, SOC, and deep discharge is prohibited when the SOC is below 20%; the continuous operating time of the generator includes, but is not limited to, the remaining fuel.

[0037] Step 2.2: Monitor the energy input status, load demand status, and device status of the energy port, load port, and solid-state relay matrix of the emergency power supply terminal, respectively. Under the set operating constraints of energy and load, acquire energy status characteristics, load demand characteristics, and solid-state relay status data, and mark the acquisition time of each characteristic. Specifically, the solid-state relay status data includes, but is not limited to: the solid-state relay's on or off status indicator ("1" represents closed, "0" represents open), the solid-state relay's redundant configuration indicator ("1" represents redundant configuration, "0" represents non-redundant configuration), operating temperature, on-state voltage drop, switch life, and voltage. Specifically, the energy state characteristics include, but are not limited to: the voltage and current of various energy inputs under the constraints of energy operation; in the embodiments, for photovoltaics, a high-precision shunt (accuracy ±1%) and differential voltage sensor are used, and a 16-bit ADC (sampling rate ≥1MSPS) is used to synchronously collect the voltage (range 0-1500V) and current (range 0-50A) output by the photovoltaic panel to realize photovoltaic power generation input state monitoring; for the energy storage battery pack inside the emergency power terminal, the total voltage (range 24-96V) and charging and discharging current (±100A) of the battery pack are monitored in real time through a Hall effect sensor to realize energy storage battery pack input state monitoring; for mains power and backup generators, a true RMS conversion chip is used to detect the input voltage (range 85-265VAC), and a phase-locked loop circuit is used to measure the frequency (range 47-53Hz) with an accuracy of ±0.1Hz to realize mains power and backup generator input state monitoring; Specifically, load demand characteristics include, but are not limited to: voltage, current, frequency, and power requirements of different types of loads, wherein the types of loads include: resistive, inductive, and capacitive. In this embodiment, the load demand status monitoring process includes: 1) Perform FFT analysis on the load current to extract harmonic characteristics: the current waveform of resistive load is in phase with the voltage and the harmonic content is <5%; the current of inductive load lags the voltage by 30-60° and contains 5th and 7th harmonics; the current of capacitive load leads the voltage by 10-20° and has a low harmonic content.

[0038] 2) The instantaneous power algorithm is used to calculate the power demand in real time.

[0039] Step 3: Utilize the energy status characteristics and load demand characteristics of each emergency power terminal to generate the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods, and generate the action command of the solid-state relay associated with the optimal energy transmission path.

[0040] Specifically, step 3 includes: Step 3.1: Pre-define multiple energy transmission paths and label the importance level of the energy load connection method corresponding to each energy transmission path; perform chromosome encoding on each energy transmission path and initialize the population to generate an initial population; Step 3.2: Construct the fitness function and establish weighting coefficients based on the importance level and state data of the solid-state relays;

[0041] In the formula, For the fitness function, Indicates energy priority indicators, This represents the load demand matching index. Indicators representing the degree of energy state matching, Indicators representing importance levels This indicates the health indicators of a solid-state relay. , , This represents the weighting coefficients determined using the entropy weighting method. This is the health penalty factor for solid-state relays when they are redundantly configured. =1, when the solid-state relay is not redundantly configured. It is an integer greater than 1, and in this example, it is taken as 2.

[0042] In this system, energy priority indicators are set for various energy sources according to their energy priority from high to low. Different energy sources have different stability, cost, and emergency adaptability. A dynamically adjustable priority ranking is preset, prioritizing the selection of high-priority energy sources to power the load. In this embodiment, the energy priority ranking is as follows: mains power (stable and low cost) > photovoltaic (clean but affected by sunlight) > energy storage battery pack (emergency backup, limited SOC) > backup generator (noisy, high fuel consumption). Therefore, the energy priority indicator for mains power is 4, the energy priority indicator for photovoltaic is 3, the energy priority indicator for energy storage battery pack is 2, and the energy priority indicator for backup generator is 1. If a high-priority energy source is unavailable (e.g., due to a mains power outage), it is automatically downgraded to a lower-priority energy source (e.g., energy storage). In a multi-directional topology, energy needs to go through conversion stages (such as AC / DC, DC / DC, DC / AC converters) from the energy source to the load. It's necessary to verify whether the solid-state relays in the path meet the load requirements. If the solid-state relays in the path do not meet the load requirements, the load requirement matching index of the path defaults to 0. If the solid-state relays in the path meet the load requirements, the load requirement matching index of the path defaults to 1. Load requirements include voltage / frequency matching; for example, if the load requires AC220V / 50Hz, then the path with this parameter should be selected (e.g., energy storage → D). C / AC converter (220V / 50Hz) → load); load type matching: for inductive loads, the solid-state relays in the path must have inrush current suppression capability (e.g., the DC / AC converter must support feedforward control to quickly compensate for reactive power demand during startup); for capacitive loads, the solid-state relays in the path must have high-frequency harmonic filtering capability (e.g., the AC / DC converter has built-in LC filter to avoid voltage spikes); power capacity matching: the rated power of the solid-state relays in the path must be greater than or equal to the real-time power of the load. For example, a 1500W load should be matched with a converter path rated at 2000W to avoid overload; The core state parameters of various energy states (photovoltaic, energy storage battery, mains power, generator) involved in the emergency power system are predefined, such as photovoltaic array: output voltage, output current, real-time power; energy storage battery: remaining power, charging and discharging current, single cell voltage; mains power: input voltage, frequency, voltage distortion rate; if there are multiple paths that meet the load demand characteristics, further optimization is carried out in combination with energy state characteristics, including: extracting various operating parameters of energy from the path with a load demand matching degree index of 1. In the embodiment, the output voltage and real-time power of the photovoltaic path are extracted as operating parameters. When the operating parameters meet the energy's operating constraints, the parameter compliance degree q=1. When the operating parameters do not meet the energy's operating constraints, the parameter compliance degree q=0. The sum of all parameter compliance degrees q is used as the energy state matching degree index. If there are multiple paths that meet the load demand characteristics and energy status characteristics, the highest importance level of the energy load connection method implemented by the energy transmission path is extracted as the importance level index. The importance level index is 4 for special level, 3 for level 1, 2 for level 2, and 1 for temporary. Among them, the weighted sum of operating temperature health, on-state voltage drop health, and switching life health is used as the health index of solid-state relays;

[0043] In the formula, For working temperature health, , , These are the maximum, initial, and actual operating temperatures of the solid-state relay, respectively. When the actual operating temperature is close to the maximum value, the operating temperature health status is 0.

[0044] In the formula, For the health status of the on-state pressure drop, , , These are the maximum, allowable, and actual on-state voltage drop values ​​for the solid-state relay, respectively. When the actual value of the on-state voltage drop is close to the maximum value, the on-state voltage drop health status is 0;

[0045] In the formula, For switch lifespan health, , These are the actual and design values ​​for the number of switching operations of the solid-state relay, respectively. When the actual number of switching cycles is close to the design value, the switch lifespan health status is 0.

[0046] In the formula, For the health indicators of solid-state relays, , , As weighting coefficients, in the example =0.45, =0.35, =0.2.

[0047] Step 3.3: For energy transmission paths that meet the operational constraints of energy and load, a multi-objective genetic algorithm is used to determine the optimal energy transmission path based on the fitness function. In this embodiment, when using a multi-objective genetic algorithm, the energy transfer path is encoded as a chromosome, and a certain number of chromosomes are randomly generated to form an initial population, with each chromosome representing a possible energy transfer path. Since an initial population is randomly generated in the initial stage, and this initial population includes a large number of candidate energy transfer paths, some paths may be impossible to implement from an engineering perspective due to violations of basic operating rules. Therefore, based on the operating constraints of energy and load, unachievable paths are eliminated to reduce the redundancy of subsequent fitness calculations and improve algorithm efficiency. For example, suppose the current MPPT effective range of photovoltaic power is DC 500-600V. Photovoltaics can only output maximum power within this voltage range; outside this range, the power is significantly reduced. If the candidate path generated in the initial population of the genetic algorithm is: "Photovoltaic (current output DC 480V) → DC / DC converter (input requires DC 500V or higher) → DC load", because the photovoltaic output voltage (480V) exceeds the effective MPPT range, violating the photovoltaic operating constraints, this path is excluded from the search boundary. The algorithm only searches for a suitable DC / DC converter or load within the effective range of "photovoltaic output DC 500-600V" to ensure that the optimized path can utilize photovoltaic power for stable power supply. Obtain the fitness function and use the tournament selection method to select chromosomes with high fitness from the current population as parents. Cross over the parent chromosomes, exchanging some genes to generate new offspring chromosomes, simulating biological gene exchange to create new energy transfer paths. Mutate the offspring chromosomes, randomly changing some genes to increase population diversity and avoid getting trapped in local optima. Repeat the above steps iterate until the termination condition is met, such as reaching the maximum number of iterations or the fitness value no longer significantly improving, and output the best energy transfer path for the day.

[0048] Step 3.4: Generate the action command of the solid-state relay associated with the optimal energy transfer path; Once the optimal energy transmission path is determined, the energy path decision module quickly generates control commands for each solid-state relay along the optimal energy transmission path. These commands are output in the form of high-speed digital signals to control the switching action of the solid-state relay matrix. In this embodiment, the optimal energy transmission path is "photovoltaic + energy storage → AC load". The energy path decision module will generate control commands to turn on the solid-state relays connecting the photovoltaic, energy storage and AC load ports, ensuring that energy can be transmitted stably and efficiently to the AC load.

[0049] Step 4: Determine the load mutation type based on the operation monitoring data of each emergency power supply terminal. If the load mutation type is a solid-state relay fault, disconnect the faulty solid-state relay. If there is a redundant solid-state relay for the faulty solid-state relay, close the redundant solid-state relay. If the load mutation type is a non-solid-state relay fault, determine the voltage compensation amount at the current moment based on the equivalent circuit of the optimal energy transmission path and upload the voltage compensation amount at the current moment to the cloud. Monitor the voltage compensation amount at subsequent moments. If, starting from subsequent moments, a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval, generate a predicted compensation voltage amount based on the voltage compensation amount at the current moment and the fixed time interval, and upload it to the cloud.

[0050] The process of initiating rapid response control includes: switching off the solid-state relay associated with the optimal energy transmission path and closing the redundant solid-state relay corresponding to the solid-state relay. The process of initiating feedforward response control includes: extracting the equivalent circuit corresponding to the optimal energy transmission path, constructing a voltage compensation model based on the equivalent circuit, obtaining the current change at the current moment, and obtaining the compensation voltage at the current moment based on the current change and the voltage compensation model. Multidimensional features are obtained by extracting features from the current solid-state relay status data. Based on the current discrete current change rate, multidimensional features and fault comparison table, the load mutation type corresponding to the discrete current change rate and multidimensional features is determined.

[0051] Specifically, step 4 includes: Step 4.1: Preset a sliding window and use the load demand characteristics within several sliding windows to calculate the voltage deviation rate and current change rate at the current moment; A preset sliding window is used to divide the load demand characteristics within the acquisition period into windows, and the load demand characteristics within several sliding windows are obtained. The load demand characteristics include voltage and current values. The sampled voltage values ​​within the first k sliding windows are obtained, and the average voltage value is obtained based on the sampled voltage values ​​within the k sliding windows. The current voltage value is compared with the average voltage value to obtain the voltage deviation rate at the current moment. The current value at the current moment is compared with the current value at the previous moment to obtain the discrete rate of change of the current at the current moment. As shown below:

[0052]

[0053] In the formula, For a moment voltage value, The average voltage. For a moment The current value, The duration of the sliding window is 1 μs in this example, and high-frequency sampling ensures accuracy. Step 4.2: Preset voltage deviation rate threshold and current change rate threshold. If the current change rate at the current moment is greater than the current change rate threshold, proceed to step 4.3 for multi-dimensional feature fusion judgment. The preset voltage deviation rate threshold and current change rate threshold are set based on the voltage deviation rate and current change rate during the normal operation of the emergency power supply terminal. In this embodiment, the voltage deviation rate threshold is 5% and the current change rate threshold is 3%. A single current change rate may lead to misjudgment. For example, there are normal current fluctuations when a capacitive load is charging. It is necessary to combine multiple characteristics such as voltage drop amplitude and harmonic content, and accurately identify the type of load change through a preset reference table, such as starting impact and short circuit fault. Step 4.3: Construct a fault reference table, which includes different current change rates and load mutation types corresponding to multidimensional features; extract features from the current solid-state relay status data to obtain multidimensional features, including but not limited to: voltage drop amplitude and harmonic content; determine the load mutation type based on the current current change rate, multidimensional features, and fault reference table. Among them, the voltage drop amplitude can be obtained from the voltage, and the harmonic content can be obtained by analyzing the voltage using FFT (Fast Fourier Transform).

[0054] Step 4.4: If the load change type is a solid-state relay fault, then disconnect the faulty solid-state relay; if there is a redundant solid-state relay for the faulty solid-state relay, then close the redundant solid-state relay. Step 4.5: If the load change type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud; the cloud sends an instruction to the corresponding controller to compensate for the phase difference between the load voltage and current based on the voltage compensation amount. The process of initiating feedforward response control includes: constructing a voltage compensation model based on the equivalent circuit of the optimal energy transfer path; determining the voltage compensation amount at the current moment based on the voltage compensation model according to the current change at the current moment, satisfying the following relationship: ,

[0055] In the formula, For a moment Voltage compensation amount, , These are the power supply internal resistance and line inductance in the equivalent circuit, respectively. For a moment The change in current, It is the steady-state current; Inductive loads in the system cause current to lag behind voltage, while capacitive loads cause current to lead voltage. Both of these will cause output voltage phase shift. By using predistortion technology to pre-adjust the phase or duty cycle of the PWM waveform, the phase difference caused by the load characteristics can be compensated to ensure that the output voltage and current are in phase.

[0056] In this invention, the composite control module utilizes a layered control approach of prediction, suppression, and fallback. Upon detecting a load surge caused by a non-solid-state relay fault based on the current change rate, it immediately triggers feedforward response control to compensate for voltage changes in advance, suppressing voltage fluctuations at the source. Simultaneously, voltage fluctuation detection serves as a fallback. If the load surge is too strong (e.g., a short circuit), or if the feedforward response control fails to completely offset the disturbance, causing the voltage deviation rate to exceed a threshold, a more forceful rapid response mechanism is triggered to ensure the load does not lose power or become damaged due to continuous voltage anomalies. Furthermore, during the current change rate detection process, multi-feature fusion judgment is used to avoid misjudgments based on a single current change rate. Through the combination of causal correlation and timing coordination, a closed-loop control is formed from the occurrence of a disturbance to output stability, improving both response speed and control accuracy. This is the core guarantee for the speed and reliability of emergency power supply systems.

[0057] Step 4.6: Mark the compensation voltage at the current moment as the ultra-short-term mutation index, monitor the subsequent moments of the ultra-short-term mutation index, and if a compensation voltage consistent with the ultra-short-term mutation index is generated at a fixed time interval starting from the subsequent moment, mark the ultra-short-term mutation index as the repeating compensation index, and generate the predicted compensation voltage corresponding to each subsequent fixed interval based on the repeating compensation index and the fixed time interval.

[0058] The above process achieves rapid response to voltage fluctuations, load changes, and solid-state relay failures through a closed loop of detection, analysis, and compensation. At the same time, it balances dynamic performance and steady-state accuracy through the synergy of feedforward response control and repetitive control.

[0059] The parameters in the formula (such as threshold, weight, and equivalent impedance) are obtained by software simulation based on a large amount of data to get a formula that is closest to the real situation. The preset parameters and preset thresholds in the formula are set by those skilled in the art based on the actual situation or obtained by simulation based on a large amount of data to ensure the practicality of the project.

[0060] In this embodiment, the system and method proposed in this invention are applied. When the energy state is characterized by fluctuations in photovoltaic power and a decrease in energy storage SOC, the load is detected to change in real time. The energy path decision module continuously updates the path through closed-loop feedback. When the energy state changes, if cloud cover causes a sudden drop in photovoltaic power, the original "photovoltaic → load" energy transmission path will obviously have insufficient power output. The system needs to switch to a combined photovoltaic and energy storage power transmission path within milliseconds to supplement the power gap through energy storage. When the load type changes, if an inductive load suddenly starts, causing an inrush current, the converter in the original path may experience a voltage drop due to current overload. The system needs to quickly switch to a converter path with surge suppression function, including enabling a larger capacity DC / AC converter and compensating for the surge current through feedforward response control. This invention utilizes the flexibility of multi-directional topology, allowing energy to flow in multiple directions, realizing a cycle of "sensing parameters → rule-based decision → topology execution → dynamic optimization". Combined with the adaptability of energy state and load type, it maximizes system efficiency and energy utilization while ensuring the reliability of emergency power supply.

[0061] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0062] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0063] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0064] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A multi-directional topology AC / DC intelligent conversion emergency power supply system, deployed in the cloud and communicating in a distributed manner with multiple emergency power supply terminals, each emergency power supply terminal including a solid-state relay matrix; characterized in that, include: The redundancy design module is used to configure redundant solid-state relays in the solid-state relay matrix of each emergency power terminal based on the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power terminal. The data acquisition module is used to collect the energy status characteristics, load demand characteristics, and solid-state relay status data of each emergency power terminal in real time under the set operating constraints of energy and load of each emergency power terminal. The energy path decision module is used to generate the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods by utilizing the energy status characteristics and load demand characteristics of each emergency power terminal, and to generate the action command of the solid-state relay associated with the optimal energy transmission path. The composite control module is used to determine the type of load mutation based on the operation monitoring data of each emergency power terminal. If the load mutation type is a solid-state relay fault, the faulty solid-state relay is disconnected. If there is a redundant solid-state relay for the faulty solid-state relay, the redundant solid-state relay is closed. If the load mutation type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud. The voltage compensation amount at the current moment is monitored at subsequent moments. If a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval starting from the subsequent moment, a predicted compensation voltage amount is generated based on the voltage compensation amount at the current moment and the fixed time interval, and uploaded to the cloud.

2. The multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 1, characterized in that, include: The redundant design module connects to the expansion terminals of the solid-state relay matrix of each emergency power supply terminal; The data acquisition module connects to the energy-side port, load-side port, and solid-state relay matrix of each emergency power terminal; Both the energy path decision module and the composite control module are connected to the drive end of the solid-state relay matrix of each emergency power supply terminal. The redundant design module transmits signals to the data acquisition module, the data acquisition module transmits signals to the energy path decision module and the composite control module, and the energy path decision module transmits signals to the composite control module; the composite control module interacts with the cloud for data exchange.

3. A method for operating a multi-directional topology AC / DC intelligent conversion emergency power supply system, implemented using the multi-directional topology AC / DC intelligent conversion emergency power supply system as described in claim 1 or 2, characterized in that... include: Obtain the historical usage frequency and historical failure frequency of various energy load connection methods implemented by each emergency power terminal, and configure redundant solid-state relays in the solid-state relay matrix of each emergency power terminal. Under the set operating constraints of energy and load for each emergency power terminal, the energy status characteristics, load demand characteristics and solid-state relay status data of each emergency power terminal are collected in real time. By utilizing the energy status characteristics and load demand characteristics of each emergency power terminal, the optimal energy transmission path for each emergency power terminal to achieve various energy load connection methods is generated, as well as the action command of the solid-state relay associated with the optimal energy transmission path is generated. The type of load mutation is determined based on the operation monitoring data of each emergency power supply terminal. If the load mutation type is a solid-state relay fault, the faulty solid-state relay is disconnected. If there is a redundant solid-state relay for the faulty solid-state relay, the redundant solid-state relay is closed. If the load mutation type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transmission path, and the voltage compensation amount at the current moment is uploaded to the cloud. The voltage compensation amount at the current moment is monitored at subsequent moments. If, starting from subsequent moments, a voltage compensation amount consistent with the voltage compensation amount at the current moment is generated at a fixed time interval, a predicted compensation voltage amount is generated based on the voltage compensation amount at the current moment and the fixed time interval, and uploaded to the cloud.

4. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 3, characterized in that, In a solid-state relay matrix, the energy load connection method associated with each solid-state relay is determined based on the energy type connected to the input terminal and the load type connected to the output terminal. The fuzzy comprehensive evaluation method is adopted to determine the importance level of various energy load connection methods based on their historical usage frequency and historical failure frequency, and then the importance level of the energy load connection method is mapped to the importance level of the associated solid-state relay. The importance level of various energy load connection methods is compared with a preset threshold, and redundant solid-state relays are configured for the solid-state relays associated with energy load connection methods whose importance level is greater than the preset threshold.

5. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 4, characterized in that, Build an online user interface, through which users can input operating constraints for energy and load; The energy input status, load demand status, and device status of the emergency power supply terminal's energy port, load port, and solid-state relay matrix are monitored respectively. Under the set operating constraints of energy and load, energy status characteristics, load demand characteristics, and solid-state relay status data are acquired, and the acquisition time of each characteristic is marked.

6. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 3, characterized in that, Multiple energy transmission paths are preset, and the importance level of the energy load connection method corresponding to each energy transmission path is marked; Each energy transport path is encoded with chromosomes and the population is initialized to generate an initial population and construct a fitness function. Based on the fitness function, a multi-objective genetic algorithm is used to determine the optimal energy transfer path under the constraints of energy and load operation.

7. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 6, characterized in that, In the formula, For the fitness function, Indicates energy priority indicators, This represents the load demand matching index. Indicators representing the degree of energy state matching, Indicators representing importance levels This indicates the health indicators of a solid-state relay. , , This represents the weighting coefficients determined using the entropy weighting method. This is the health penalty factor for solid-state relays when they are redundantly configured. =1, when the solid-state relay is not redundantly configured. It is an integer greater than 1.

8. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 7, characterized in that, The energy priority index for mains power is 4, for photovoltaic power is 3, for energy storage battery packs is 2, and for backup generators is 1. If the solid-state relays in the path do not meet the load demand characteristics of the load, the load demand matching index of the path is 0; if the solid-state relays in the path meet the load demand characteristics of the load, the load demand matching index of the path is 1. Extract various operating parameters of energy from the path where the load demand matching degree index is 1. When the operating parameters meet the operating constraints of energy, the parameter compliance degree q=1. When the operating parameters do not meet the operating constraints of energy, the parameter compliance degree q=0. The sum of all parameter compliance degrees q is used as the energy state matching degree index. If there are multiple paths that meet the load demand characteristics and energy status characteristics, the highest importance level of the energy load connection method implemented by each energy transmission path is extracted as the importance level index. The importance level index value is 4 for special importance, 3 for first importance, 2 for second importance, and 1 for temporary importance.

9. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 7, characterized in that, The weighted sum of operating temperature health, on-state voltage drop health, and switching life health is used as the health index of solid-state relays; In the formula, For working temperature health, , , These are the maximum, initial, and actual operating temperatures of the solid-state relay, respectively. In the formula, For the health status of the on-state pressure drop, , , These are the maximum, allowable, and actual on-state voltage drop values ​​for the solid-state relay, respectively. In the formula, For switch lifespan health, , These are the actual and design values ​​for the number of switching operations of the solid-state relay, respectively. In the formula, For the health indicators of solid-state relays, , , These are the weighting coefficients.

10. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 3, characterized in that, A preset sliding window is used to calculate the voltage deviation rate at the current moment by utilizing the load demand characteristics within several sliding windows. and rate of change of current As shown below: In the formula, For a moment voltage value, The average voltage. For a moment The current value, The duration of the sliding window; Preset voltage deviation rate threshold and current change rate threshold. If the current change rate at the current moment is greater than the current change rate threshold, then perform multi-dimensional feature fusion judgment. A fault comparison table is constructed, which includes different current change rates and load mutation types corresponding to multidimensional features; feature extraction is performed on the current solid-state relay status data to determine multidimensional features; Based on the current rate of change, multidimensional characteristics, and fault comparison table at the current moment, determine the type of load mutation.

11. The operating method of the multi-directional topology AC / DC intelligent conversion emergency power supply system according to claim 10, characterized in that, If the load change type is a non-solid-state relay fault, the voltage compensation amount at the current moment is determined based on the equivalent circuit of the optimal energy transfer path, and the voltage compensation amount at the current moment is uploaded to the cloud; the cloud sends an instruction to the corresponding controller to compensate for the phase difference between the load voltage and current based on the voltage compensation amount. The voltage compensation at the current moment satisfies the following relationship: ， In the formula, For a moment Voltage compensation amount, , These are the power supply internal resistance and line inductance in the equivalent circuit, respectively. For a moment The change in current, This is the steady-state current.

12. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 3-11.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 3-11.

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