Adaptive control system for AC / DC power supply in microgrid

Abstract

This invention provides an adaptive control system for AC / DC power supply in a microgrid, relating to the field of power system technology. It includes: a data acquisition module for real-time acquisition of AC / DC power supply operating parameters via local sensors, generating raw operating data including voltage, current, frequency, and power information; a command generation module for generating initial power allocation commands based on the raw operating data and a preset droop characteristic calculation strategy; and an evaluation and adjustment module for analyzing the operating state characteristics of the initial power allocation commands, establishing a reference benchmark, and determining the evaluation direction to construct a state determination interval. Monitoring units are set up inside and outside the state determination interval, and an evaluation trajectory is generated based on the time-series change characteristics of the parameters to calculate the adaptive adjustment amount and obtain control parameter correction commands. This invention adapts in real-time to the AC / DC hybrid operation of the microgrid, dynamically adjusting the AC / DC power output and control parameters, thereby improving the operational stability of the microgrid.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to an adaptive control system for AC / DC power supply in a microgrid. Background Technology

[0002] In a microgrid in an industrial park, traditional control technologies have some shortcomings. For example, when the demand for DC loads in the industrial park suddenly increases significantly during a certain period, traditional control strategies mostly adjust based on fixed power-voltage and power-frequency relationships. This may not be able to quickly and accurately allocate the power of the DC power supply to the level that meets the demand of the new load, causing the DC bus voltage to drop rapidly. On the AC subgrid side, due to the difficulty in taking into account the dynamic coordination of AC and DC subgrids, the AC frequency may fluctuate unnecessarily, affecting the stable operation of the AC load.

[0003] Furthermore, when encountering sudden weather changes and drastic fluctuations in the output power of photovoltaic panels, traditional control technologies are generally slow to respond in adjusting the output power of AC and DC power supplies to balance power deficits or surpluses. When dealing with complex and rapidly changing power fluctuations, they rely on relatively fixed communication and control processes and cannot change control parameters in a timely manner according to real-time operating conditions. This causes the microgrid to be in a state of power imbalance for a long time, which not only affects power quality but may also shorten the service life of power supply equipment due to overload or underload operation of some power sources. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an adaptive control system for AC and DC power supply in a microgrid, so as to realize the adaptation and stable regulation of AC and DC power supply, and improve the operational stability and anti-interference capability of the microgrid.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: The first aspect is the adaptive control system for AC / DC power supply in a microgrid, including: The data acquisition module is used to collect the operating parameters of AC / DC power supply in real time through local sensors and generate raw operating data including voltage, current, frequency and power information. The instruction generation module is used to generate initial power allocation instructions based on the original operating data and through a preset droop characteristic calculation strategy. The evaluation and adjustment module is used to analyze the operating status characteristics of the initial power allocation command, establish a reference benchmark and determine the evaluation direction to construct the state judgment interval; monitoring units are set up inside and outside the state judgment interval, and evaluation trajectory is generated by combining the time-series change characteristics of parameters to calculate the adaptive adjustment amount and obtain the control parameter correction command. The monitoring and triggering module is used to monitor the power communication status according to the control parameter correction command, and generate a control transfer trigger signal when a communication abnormality is detected. The election and switching module is used to elect a dominant power supply unit according to preset rules based on the real-time comparison results of the output current of each power supply unit when a control transfer trigger signal is detected, and to generate a control switching command. The analysis and compensation module is used to analyze the dynamic response characteristics of AC and DC power supplies in real time in response to control switching commands, and generate a damping compensation control signal when oscillation characteristics are identified. The parameter adjustment module is used to monitor the actual operating conditions of the microgrid and dynamically adjust the power control parameters based on the damping compensation control signal to achieve the final power distribution.

[0006] In a second aspect, a computing device includes: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, enable the one or more processors to implement the system.

[0007] Thirdly, a computer-readable storage medium storing a program that, when executed by a processor, implements the system.

[0008] The above-described solution of the present invention has at least the following beneficial effects: It captures core parameters such as voltage, current, frequency, and power of AC / DC power supplies in real time, and generates initial power allocation commands by combining preset droop characteristic calculation strategies, enabling rapid response to load changes and power output fluctuations. By constructing dynamic judgment intervals for power and voltage and generating evaluation trajectories based on parameter time-series changes, it can accurately identify operating states deviating from the reference benchmark and calculate adaptive adjustment amounts, ensuring stable power supply quality. Addressing common issues in microgrids such as communication link interruptions, excessive latency, and increased bit error rates, it monitors the communication status of each power supply unit in real time based on control parameter correction commands, and immediately generates a control transfer trigger signal upon identifying an anomaly. By comparing the output current of each power supply unit, it quickly elects a dominant power supply unit according to rules and completes the control switch, ensuring that the microgrid can still maintain basic power supply functions under extreme communication failures, improving anti-interference capabilities and operational reliability.

[0009] During dynamic processes such as control switching, microgrids are prone to power oscillations due to sudden changes in power output. If not suppressed in time, these oscillations may lead to voltage collapse, equipment damage, and other cascading failures. Real-time acquisition of dynamic response data from AC and DC power supplies is used to identify oscillation characteristics through time-domain waveform analysis. Based on the oscillation amplitude and frequency, damping compensation control signals are generated to dynamically adjust power control parameters, rapidly attenuating the oscillation amplitude and shortening its duration, preventing the oscillation from spreading to the entire microgrid. This ensures stable operation under complex conditions such as topology changes, load surges, and control switching. Through adaptive adjustment calculations and damping compensation control mechanisms, sudden changes in power unit output are avoided, reducing mechanical stress and electrical shocks during equipment operation, extending the service life of critical equipment such as inverters, energy storage batteries, and transformers, and lowering equipment replacement costs. Attached Figure Description

[0010] Figure 1 This is a flowchart illustrating the AC / DC power supply adaptive control system for a microgrid provided in an embodiment of the present invention.

[0011] Figure 2 This is a schematic diagram of an embodiment of the present invention, which uses a damping compensation control signal to monitor the actual operating conditions of a microgrid and dynamically adjust power control parameters to achieve the final power distribution. Detailed Implementation

[0012] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0013] like Figure 1 As shown, embodiments of the present invention propose an AC / DC power supply adaptive control system for a power system in a microgrid, comprising: The data acquisition module is used to collect the operating parameters of AC / DC power supply in real time through local sensors and generate raw operating data including voltage, current, frequency and power information. The instruction generation module is used to generate initial power allocation instructions based on the original operating data and through a preset droop characteristic calculation strategy. The evaluation and adjustment module is used to analyze the operating status characteristics of the initial power allocation command, establish a reference benchmark and determine the evaluation direction to construct the state judgment interval; monitoring units are set up inside and outside the state judgment interval, and evaluation trajectory is generated by combining the time-series change characteristics of parameters to calculate the adaptive adjustment amount and obtain the control parameter correction command. The monitoring and triggering module is used to monitor the power communication status according to the control parameter correction command, and generate a control transfer trigger signal when a communication abnormality is detected. The election and switching module is used to elect a dominant power supply unit according to preset rules based on the real-time comparison results of the output current of each power supply unit when a control transfer trigger signal is detected, and to generate a control switching command. The analysis and compensation module is used to analyze the dynamic response characteristics of AC and DC power supplies in real time in response to control switching commands, and generate a damping compensation control signal when oscillation characteristics are identified. The parameter adjustment module is used to monitor the actual operating conditions of the microgrid and dynamically adjust the power control parameters based on the damping compensation control signal to achieve the final power distribution.

[0014] In this embodiment of the invention, core operating parameters such as voltage, current, frequency, and power are collected in real time by local sensing devices. This allows for the immediate capture of the actual operating status of the AC / DC power supply. The generated raw operating data is comprehensive and closely matches real-world operating conditions, preventing control commands from deviating from actual requirements due to data lag or missing data. Based on the raw operating data, an initial power allocation command is generated using a preset droop characteristic calculation strategy. This allows for precise matching of the active and reactive power allocation ratios according to the voltage and frequency deviations of each AC / DC power supply unit, avoiding overload or light load situations for a single power supply. This enables each power supply unit to participate in power supply in an adapted state from the initial stage, improving the overall energy utilization efficiency of the microgrid. The initial power allocation command is analyzed for operating status characteristics. By establishing a reference benchmark, constructing a state judgment interval, and generating an evaluation trajectory, the dynamic changing trends of parameters such as power and voltage can be monitored in real time. The adaptive adjustment amount can be accurately calculated and the control parameters corrected. This process can promptly correct parameter deviations, maintaining stable operation even under conditions such as load fluctuations and changes in power supply characteristics, thus improving the adaptability to complex operating conditions.

[0015] Based on the control parameter correction command, the power communication status is monitored, and abnormal situations such as excessive communication delay, insufficient transmission rate, and excessive bit error rate can be identified in a timely manner. The control transfer trigger signal is generated quickly, and the dominant power supply is selected by combining the real-time comparison results of the output current of each power unit. This ensures that the control is switched quickly when an abnormality occurs, avoids system paralysis due to communication problems, and ensures the continuity of power supply to the microgrid. During the control switching process, the dynamic response characteristics of AC and DC power supplies are analyzed in real time. Once power oscillation characteristics are identified, a damping compensation control signal is generated immediately to alleviate voltage and power fluctuations caused by sudden changes in power output characteristics during the switching process, and to prevent the oscillation from spreading and affecting the overall stability of the system.

[0016] In a preferred embodiment of the present invention, generating an initial power allocation command based on the original operating data and through a preset droop characteristic calculation strategy may include: In this embodiment of the invention, the original operating data of each AC / DC power supply unit in the microgrid is obtained, including the actual voltage value and the actual frequency value. Specifically, this includes: identifying all AC / DC power supply units participating in power distribution in the microgrid system, such as AC generators, DC energy storage batteries, and photovoltaic inverters; determining a unique identifier for each power supply unit to avoid subsequent data confusion; and then, using microgrid monitoring equipment, such as voltage sensors and frequency sensors, to collect real-time data from each power supply unit. For AC power supply units, the voltage sensor measures the actual voltage value at their output terminal, such as the actual value of the current output voltage of an AC generator; the frequency sensor measures the actual frequency value of the AC power output by the AC power supply unit. For DC power supply units, the voltage sensor measures the actual DC voltage value at their output terminal. Since DC power has no frequency attribute, its actual frequency value can be determined according to system preset rules, such as uniformly setting it to 0 or other specific reference values, to ensure that all power supply units have complete actual voltage and frequency value data. Finally, the data is compiled into an original operating dataset including the identifier of each power supply unit, the corresponding actual voltage value, and the actual frequency value.

[0017] The actual voltage and frequency values ​​are compared with preset voltage and frequency reference values ​​to obtain voltage and frequency deviation values. Specifically, this involves retrieving voltage and frequency reference values ​​for each AC / DC power supply unit from the system's preset parameter library. These reference values ​​are preset according to the microgrid's design requirements, operating standards, and rated parameters of each power supply unit. Different types and specifications of power supply units may have different reference values. For example, the voltage reference value of an AC generator is set to 380V and the frequency reference value is set to 50Hz; the voltage reference value of a DC energy storage battery is set to 220V and the frequency reference value is set to 0Hz.

[0018] For each power supply unit, a voltage deviation value is calculated by subtracting its corresponding voltage reference value from the actual voltage value of the power supply unit. The result is the voltage deviation value of the power supply unit. If the actual voltage value is higher than the reference value, the voltage deviation value is positive; if the actual voltage value is lower than the reference value, the deviation value is negative; if the two are equal, the deviation value is 0. A frequency deviation value is then calculated. For AC power supply units, the actual frequency value is subtracted from the preset frequency reference value to obtain the frequency deviation value. The calculation logic for the actual value and the reference value is followed, and the result can be positive, negative, or zero. For DC power supply units, since their actual frequency value is preset to a specific reference value, and the frequency reference value is also set to the same reference value, the frequency deviation value calculation result for DC power supply units is always 0, that is, the actual frequency value (0Hz) minus the frequency reference value (0Hz) equals 0Hz. A corresponding deviation value file is established for each power supply unit, recording its voltage deviation value and frequency deviation value.

[0019] Based on the voltage and frequency deviation values, the active power deviation and reactive power deviation values ​​corresponding to each power supply unit are calculated. Specifically, this includes: first, determining the preset power deviation calculation coefficient in the microgrid system. This coefficient is a fixed coefficient determined based on parameters such as the type of power supply unit, AC or DC, rated power, and regulation capability. Each power supply unit corresponds to an independent set of active power deviation calculation coefficients and reactive power deviation calculation coefficients. When calculating the active power deviation value, the frequency deviation value is used as the basis. The frequency deviation value of each power supply unit is multiplied by the active power deviation calculation coefficient corresponding to that unit. The product is the active power deviation value of that power supply unit. For example, if the frequency deviation value of an AC power supply unit is 0.2Hz, and its corresponding active power deviation calculation coefficient is 50kW / Hz, then the active power deviation value of that unit is 0.2×50=10kW. If the frequency deviation value is negative, the calculation result is also negative, representing the amount of active power that needs to be reduced.

[0020] When calculating the reactive power deviation, the voltage deviation is used as the basis. The voltage deviation of each power supply unit is multiplied by the reactive power deviation calculation coefficient corresponding to that unit. The product is the reactive power deviation of that power supply unit. For example, if the voltage deviation of an AC power supply unit is 5V and the corresponding reactive power deviation calculation coefficient is 20kvar / V, then the reactive power deviation of that unit is 5×20=100kvar. If the voltage deviation is negative, the reactive power deviation is also negative, which means that the reactive power needs to be reduced. For DC power supply units, since their reactive power is zero, the reactive power deviation is directly set to zero during calculation and only participates in the calculation of the active power deviation.

[0021] The active power deviation and reactive power deviation values ​​are input into the preset active frequency droop characteristic relationship and reactive voltage droop characteristic relationship of each power supply unit. The initial active power command value and initial reactive power command value of each unit are calculated and generated respectively. Specifically, this includes: firstly, retrieving the preset active frequency droop characteristic relationship and reactive voltage droop characteristic relationship of each power supply unit from the characteristic parameter library of the microgrid system. The active frequency droop characteristic relationship is a preset curve or numerical correspondence table describing the corresponding change between the active power output of the power supply unit and the frequency deviation. For example, the active frequency droop characteristic relationship of a certain power supply unit stipulates that for every 0.1Hz frequency deviation, the active power output is adjusted by 8kW. The reactive voltage droop characteristic relationship is a numerical correspondence table describing the corresponding change between the reactive power output of the power supply unit and the voltage deviation. For example, the reactive voltage droop characteristic relationship of a certain power supply unit stipulates that for every 3V voltage deviation, the reactive power output is adjusted by 50kvar.

[0022] For calculating the initial active power command value, the previously obtained active power deviation value of each power supply unit is substituted into the active power frequency droop characteristic relationship of that unit. If a numerical correspondence table is used, the corresponding active power adjustment amount is directly looked up in the table according to the active power deviation value. Then, the rated active power value of the power supply unit is added to the active power adjustment amount, and the result is the initial active power command value of the unit. If the active power adjustment amount is positive, the initial active power command value is higher than the rated active power; if the adjustment amount is negative, the initial active power command value is lower than the rated active power.

[0023] For the calculation of the initial reactive power command value, only for AC power supply units, the reactive power deviation value is substituted into the preset reactive voltage droop characteristic relationship. By looking up the value correspondence table, the reactive power adjustment amount is determined. Then, the rated reactive power value of the AC power supply unit is added to the reactive power adjustment amount to obtain the initial reactive power command value. Since the DC power supply unit has no reactive power output, its initial reactive power command value is directly set to zero.

[0024] The initial active power command and initial reactive power command values ​​of all power supply units are integrated to generate the initial power allocation command for the microgrid. Specifically, this involves: first, summing the initial active power command values ​​of all AC and DC power supply units to obtain a total sum; then comparing this sum with the current total load active power demand of the microgrid; if the difference between the sum and the total load active power demand is within a preset allowable error range (e.g., the error does not exceed 2% of the total load active power demand), the initial active power command values ​​of each unit are directly retained; if the difference exceeds the allowable error range, the initial active power command values ​​of each unit need to be adjusted proportionally. For example, if the sum is higher than the total load active power demand, the initial active power command value of each unit is reduced proportionally until the adjusted sum equals the total load active power demand. The difference between the active power demand and the initial reactive power command value meets the allowable error requirement. For the initial reactive power command value, only the AC power supply units are summarized, and the sum of their initial reactive power command values ​​is compared with the current total load reactive power demand of the microgrid. Following the same adjustment logic as the active power command value, a proportional adjustment is made when the difference exceeds the allowable error range to ensure that the sum of the initial reactive power command values ​​of the AC power supply units matches the total load reactive power demand. The adjusted initial active power command values ​​of all power supply units and the initial reactive power command values ​​of the AC power supply units are classified and organized by power supply unit number to form a complete command list containing the power supply unit number, initial active power command value, initial reactive power command value, and DC power supply units marked as zero. This list is the initial power allocation command of the microgrid.

[0025] By identifying each AC / DC power supply unit and collecting complete actual voltage and frequency values, calculation errors caused by data confusion or missing data are avoided, laying a reliable data foundation for the generation of the initial power allocation command and improving the traceability of microgrid operation data. The actual voltage and frequency values ​​are compared with preset reference values ​​to calculate deviations, which intuitively reflects the difference between the current operating state and the ideal operating state of each power supply unit. Specific frequency benchmark and reference values ​​are set for DC power supply units, ensuring that DC power supply units can be included in a unified deviation calculation system along with AC power supply units. This achieves collaborative calculation of all power supply units in the AC / DC hybrid microgrid and improves the compatibility of the calculation system. The initial power command value is calculated using preset active power frequency droop characteristics and reactive power voltage droop characteristics, fully combining the hardware performance and regulation capabilities of each power supply unit. This ensures that the calculated command value is within the safe operating range of the power supply unit, avoiding equipment damage or operational failure due to the command value exceeding the rated regulation capability of the power supply unit. In a preferred embodiment of the present invention, performing operational state characteristic analysis on the initial power allocation command, establishing a reference benchmark, and determining the evaluation direction to construct a state determination interval may include: In this embodiment of the invention, based on the initial power allocation command, the time-series characteristics of the power command value and voltage command value changing over time are extracted to obtain the dynamic change sequence of power and voltage. Specifically, this includes: determining the time range and sampling interval for data extraction; the time range is set to a continuous 10 minutes after the initial power allocation command is generated; and the sampling interval is set to once every 10 seconds to ensure that the short-term changing trends of power and voltage parameters can be fully captured, while avoiding computational redundancy due to excessive data volume; and retrieving the power command values ​​of all power supply units corresponding to the initial power allocation command from the microgrid central database, including active power command value and reactive power command value. For power and voltage command values, a raw data list is created in chronological order. For the extraction of the time-series characteristics of power command values, taking the active power command value of a certain power supply unit as an example, starting from second 0, the active power command value of the unit is recorded once every 10 seconds. A total of 60 data points are recorded within 10 minutes to form a list corresponding to time and active power command values. For example, second 0 is 500kW, second 10 is 502kW, second 20 is 498kW, and so on, second 600 is 501kW. For reactive power command values, only AC power supply units are recorded in the same way, and 60 data points are recorded to form a time-series table of reactive power command values.

[0026] For the extraction of voltage command value timing characteristics, 60 voltage command value data points for each power supply unit are recorded at 10-second intervals to form a time-to-voltage command value correspondence list. For example, for a DC power supply unit, the voltage is 380V at second 0, 381V at second 10, and so on, up to 379V at second 600. The active power, reactive power (AC), and voltage command value timing series tables for each power supply unit are sorted and organized according to the power supply unit number and parameter type to obtain an independent dynamic change sequence for each parameter. For example, the active power dynamic change sequence for AC power supply unit #1, the voltage dynamic change sequence for DC power supply unit #2, etc. Each sequence contains complete data of 60 time points and corresponding parameter values.

[0027] Based on the dynamic change sequences of power and voltage, statistical benchmark values ​​are calculated over a period of time to establish power and voltage reference benchmarks. Specifically, this includes: for each dynamic change sequence, determining a statistical calculation time window of 10 minutes and 60 data points, and using a weighted average method after removing extreme values ​​to calculate the statistical benchmark value to reduce the impact of abnormal data on the benchmark value; from the dynamic change sequence of active power of a certain power unit, identifying the maximum and minimum values ​​among the 60 data points, removing these two extreme values ​​from the sequence, and retaining 58 data points as valid calculation data. For example, if the maximum value in the sequence is 520kW and the minimum value is 480kW, after removing these extreme values, 58 data points between 482kW and 518kW are retained.

[0028] Weights are assigned based on the order of data collection time, with data closer to the current moment having a greater impact on the benchmark value. The weighting coefficients are set linearly increasing. The 60 raw data points are divided into 10 groups of 6 data points each. In the first group, the earliest 6 data points have a weighting coefficient of 0.8, in the second group it is 0.85, and so on, until the 10th group, where the latest 6 data points have a weighting coefficient of 1.2, ensuring that the weight of the latest data is 50% higher than that of the earliest data. For each valid data point, its value is multiplied by the weighting coefficient of the corresponding time group to obtain the weighted value of each data point. The weighted values ​​of all valid data points are summed to obtain the weighted sum. At the same time, the weighting coefficients corresponding to all valid data points are summed to obtain the weighted sum. Finally, the weighted sum is divided by the weighted sum to obtain the active power statistical benchmark value of the power unit, which is the active power benchmark in the power reference benchmark. For example, if the weighted sum of 58 valid data points is 28900kW and the weighted sum is 65.2, then the active power benchmark is 28900÷65.2≈443.25kW.

[0029] Using the same extreme value removal and weighted averaging method as the power reference benchmark, the maximum and minimum values ​​are removed from the voltage dynamic change sequence, leaving 58 valid data points. Weighting coefficients are set in 10 groups according to time sequence, increasing linearly from 0.8 to 1.2. The weighted value, weighted sum, and weighted sum of each valid data point are calculated. The final weighted sum divided by the weighted sum of the weights yields the voltage statistical reference value, which is the voltage reference benchmark. For example, if the weighted sum of the valid voltage data for an AC power supply unit is 21800V and the weighted sum is 58.5, then the voltage reference is 21800÷58.5≈372.65V. The arithmetic mean of the active power references of all power supply units is taken to obtain the overall active power reference benchmark of the microgrid system. The arithmetic mean of the reactive power references of the AC power supply units is taken to obtain the system reactive power reference benchmark. The arithmetic mean of the voltage references of all power supply units is taken to obtain the system voltage reference benchmark, forming a complete power reference benchmark system containing active, reactive, and voltage reference benchmarks.

[0030] Based on power and voltage reference benchmarks, and considering the operational constraints of AC and DC power sources in the microgrid, allowable positive and negative deviation thresholds for power and voltage are set to determine the allowable deviation range. Specifically, this includes: firstly, clarifying the operational constraints of AC and DC power sources in the microgrid; for AC power sources, specifying power constraints (e.g., a maximum output power of 100kW and a minimum stable output power of 10kW for photovoltaic inverters) and voltage constraints (e.g., an allowable voltage fluctuation range of 380V±5%) on the AC side); and for DC power sources, such as energy storage batteries and DC loads, specifying power constraints (e.g., a maximum charging and discharging power of 50kW and a minimum charging and discharging power of 5kW for energy storage batteries) and voltage constraints (e.g., an allowable voltage fluctuation range of 750V±8%) on the DC bus. When setting the allowable positive and negative deviation thresholds for power, the power reference benchmark is used as a basis, combined with the power constraints mentioned above: The positive deviation threshold, which is the maximum allowable power command value to exceed the reference, is calculated as follows: First, the difference between the maximum output power of the power supply and the power reference reference is taken. For example, if the maximum output of the photovoltaic inverter is 100kW and the power reference is 49kW, the difference is 51kW. Then, a safety margin is considered, usually 80%-90% of the difference is taken to avoid approaching the limit value and causing equipment overload. Here, 90% is taken, so the positive deviation threshold = 51kW × 90% ≈ 45.9kW, which is finally rounded to 46kW. The negative deviation threshold is the maximum allowable power command value to be lower than the reference: First, take the difference between the power reference and the minimum stable output power of the power supply. For example, if the minimum output of the photovoltaic inverter is 10kW, the difference is 49kW-10kW=39kW. Also, considering the safety margin, take 90%, then the negative deviation threshold = 39kW×90%≈35.1kW, which is rounded up to 35kW. When setting the allowable positive and negative deviation thresholds for voltage, the voltage reference base is used as a basis, combined with voltage constraints: Positive deviation threshold: Take the difference between the maximum allowable voltage of the power supply and the voltage reference. For example, the maximum allowable voltage on the AC side is 380V × 1.05 = 399V. The difference is 399V - 380V = 19V. With a safety margin of 90%, the positive deviation threshold is 19V × 90% ≈ 17.1V, which is rounded up to 17V. Negative deviation threshold: Take the difference between the voltage reference and the minimum allowable voltage of the power supply. For example, the minimum allowable voltage on the AC side is 380V × 0.95 = 361V. The difference is 380V - 361V = 19V. Taking a safety margin of 90%, the negative deviation threshold is 19V × 90% ≈ 17.1V. Rounded to 17V, the final power allowable deviation range is -35kW to +46kW, and the voltage allowable deviation range is -17V to +17V.

[0031] Based on the allowable positive and negative deviation thresholds, the positive and negative deviation evaluation directions of power and voltage relative to the reference standard are determined, specifically including: Regarding the power deviation assessment: Positive Deviation Assessment Direction: When the real-time power command value is higher than the power reference baseline, determine the core indicators to be assessed. First, determine whether the real-time power value and the power reference baseline exceed the positive deviation threshold (46kW). If they do, further assess whether the deviation causes the power supply to exceed the maximum output power. For example, if the real-time power is 96kW, the reference is 49kW, and the deviation is 47kW > 46kW, check whether it is close to the maximum output of the photovoltaic inverter of 100kW to avoid overload. At the same time, assess the duration of the deviation, such as whether the deviation exceeds the threshold for more than 5 seconds. If it does, an adjustment command needs to be triggered. Negative Deviation Assessment Direction: Determine the core indicators to be assessed when the real-time power command value is lower than the power reference baseline. Determine whether the power reference baseline and the real-time power value exceed the negative deviation threshold (35kW). If they do, assess whether it is lower than the minimum stable output power of the power supply. For example, if the real-time power is 8kW, the reference is 49kW, and the deviation is 41kW > 35kW, check whether it is lower than the minimum output of the photovoltaic inverter of 10kW to avoid equipment shutdown. At the same time, assess the impact on the load power supply, such as whether the deviation causes insufficient load power and whether the backup power supply needs to be started. Regarding voltage deviation assessment: Positive deviation assessment direction: Determine whether the real-time voltage value exceeds the positive deviation threshold (17V) of the voltage reference. If it does, for example, if the real-time voltage is 398V and the reference voltage is 380V, the deviation is 18V > 17V. It is necessary to assess whether it exceeds the insulation withstand voltage of the equipment to avoid insulation damage or whether it will cause overload burnout. For example, the upper limit of the allowable voltage for precision equipment is 395V. Negative deviation assessment direction: Determine whether the voltage reference and real-time voltage values ​​exceed the negative deviation threshold (17V). If they do, for example, if the real-time voltage is 362V and the reference voltage is 380V, the deviation is 18V > 17V. It is necessary to assess whether this will cause difficulty in starting the motor, insufficient torque due to low voltage, or affect the charging efficiency of the energy storage battery due to low voltage and low charging current.

[0032] Using the power reference benchmark and voltage reference benchmark as the center and the allowable deviation range as the boundary, a power dynamic range and a voltage dynamic range for real-time status determination are constructed. Specifically, when constructing the power dynamic range, the power reference benchmark (49kW) is used as the center, and the allowable deviation range (-35kW~+46kW) is used as the range boundary. The lower limit of the range = power reference benchmark - negative deviation threshold = 49kW - 35kW = 14kW; the upper limit of the range = power reference benchmark + positive deviation threshold = 49kW + 46kW = 95kW; the final power dynamic range is 14kW~95kW. This range is used for real-time determination. When the real-time power command value falls within 14kW~95kW, the power operation status is determined to be normal; if it exceeds, it is determined to be abnormal and subsequent adjustments need to be triggered. When constructing the voltage dynamic range, the voltage reference benchmark (3... Centered on 80V, and considering the allowable deviation range (-17V to +17V), the lower limit of the range = voltage reference base - negative deviation threshold = 380V - 17V = 363V; the upper limit of the range = voltage reference base + positive deviation threshold = 380V + 17V = 397V; the final voltage dynamic range is 363V to 397V, used for real-time judgment. If the real-time voltage command value is within this range, the voltage status is normal; if it exceeds this range, it is abnormal. At the same time, the dynamic update mechanism of the range needs to be clearly defined. The power / voltage reference base is recalculated every 10 minutes, and the deviation threshold and dynamic range are updated synchronously. For example, if the new power base becomes 52kW and the positive deviation threshold is adjusted to 44kW, the range is updated to 52kW - 35kW = 17kW to 52kW + 44kW = 96kW, ensuring that the range matches the real-time operating status of the microgrid.

[0033] By collecting power and voltage command values ​​at fixed time intervals and forming a sequence, the system can fully capture the time-dimensional change trend of command values, avoiding static analysis bias caused by using data from a single time point. It strongly correlates the deviation threshold with the operating constraints of AC / DC power supplies and reserves a safety margin to prevent command values ​​from exceeding the physical limits of the equipment, ensuring that the equipment operates within a stable operating range. At the same time, positive and negative thresholds are set separately, allowing for the development of protection strategies for both excessively high and excessively low abnormal scenarios. The system clarifies the evaluation focus of positive and negative deviations, avoiding inefficient indiscriminate inspections. The dynamic range centered on the benchmark and bounded by the deviation threshold can intuitively present the normal operating range. Real-time judgment only requires comparing the real-time value with the range boundary, making the operation simple and fast, and meeting the real-time control requirements of microgrids. In a preferred embodiment of the present invention, a monitoring unit is set inside and outside the state determination interval, and an evaluation trajectory is generated by combining the time-series change characteristics of the parameters to calculate the adaptive adjustment amount and obtain the control parameter correction command, which may include: In this embodiment of the invention, monitoring units are arranged at the inner and outer boundaries of the power dynamic range and the voltage dynamic range, respectively, to form a multi-layer monitoring structure. Specifically, this includes: based on the established power dynamic range, such as 14kW~95kW and voltage dynamic range, such as 363V~397V, first determining the specific locations of the inner and outer boundaries: Internal boundaries: The upper and lower limits of the range are indented by a certain percentage, usually 10% of the total width of the range, to ensure that it is within the normal range and close to the boundary. Taking the power range as an example, the total width = 95kW - 14kW = 81kW, the indentation value = 81kW × 10% ≈ 8.1kW. Therefore, the internal boundary of the power range is: lower limit side 14kW + 8.1kW ≈ 22.1kW, upper limit side 95kW - 8.1kW ≈ 86.9kW. The total width of the voltage range = 397V - 363V = 34V, the indentation value = 34V × 10% ≈ 3.4V. The internal boundary of the voltage range is: lower limit side 363V + 3.4V ≈ 366.4V, upper limit side 397V - 3.4V ≈ 393.6V.

[0034] External boundaries: Take the same proportion (10%) to extend outward from the upper and lower limits of the interval to ensure coverage of the area just beyond the interval. The power external boundary is: lower limit side 14kW-8.1kW≈5.9kW, upper limit side 95kW+8.1kW≈103.1kW; the voltage external boundary is: lower limit side 363V-3.4V≈359.6V, upper limit side 397V+3.4V≈400.4V.

[0035] Subsequently, monitoring units were deployed at each boundary location. One monitoring unit was placed at each of the inner lower boundary, inner upper boundary, outer lower boundary, and outer upper boundary of each interval, resulting in a total of 4 power intervals corresponding to 22.1kW, 86.9kW, 5.9kW, and 103.1kW, and 4 voltage intervals corresponding to 366.4V, 393.6V, 359.6V, and 400.4V, forming a double-layer monitoring structure with inner and outer layers. At the same time, an additional monitoring unit was added at the center of the interval for the power reference of 49kW and the voltage reference of 380V to capture the initial trend of parameter deviation from the reference. The final total number of monitoring units was 5 for power and 5 for voltage, totaling 10.

[0036] Utilizing a multi-layer monitoring structure, power and voltage parameters are acquired in real time, and their time-series characteristics over time are obtained to generate operational status assessment trajectories for power and voltage. Specifically, this involves: using 10 monitoring units to collect data and generate trajectories; setting the acquisition frequency, typically 0.5 seconds / time based on the microgrid's response speed, to ensure the capture of rapid changes; each monitoring unit only records data when the parameter value passes through its own position, for example, when the power reaches 22.1kW, the lower boundary monitoring unit records time point T1 + power 22.1kW; no data is recorded when the power value has not passed through, reducing redundant data; in addition to the monitoring unit's position, power and voltage values ​​at all time points within the interval are synchronously acquired (0.5 seconds / time), for example, at time T0, the power is 49... Data is collected in kW (center), 52kW at time T0.5, 55kW at time T1, etc., to ensure data coverage of the entire operating range. All collected data are sorted chronologically to form time-power datasets, such as T0:49kW, T0.5:52kW, T1:55kW, T1.5:86.9kW... and time-voltage datasets, such as T0:380V, T0.5:382V, T1:385V... Each dataset contains two fields: a timestamp accurate to 0.1 seconds and the corresponding parameter value. With time as the horizontal axis and parameter value as the vertical axis, each time parameter point in the dataset is marked on the coordinate system, and then adjacent points are connected by straight lines to form a continuous trend that intuitively reflects the path of parameter change over time.

[0037] Based on the operational status evaluation trajectory, the degree of deviation and trend of change of the reference baseline are analyzed, and the required adaptive adjustment is calculated to obtain the control parameter correction command. Specifically, this includes: based on the evaluation trajectory, taking the difference between the parameter value at the current time point in the trajectory and the reference baseline. For example, if the current power is 103.1kW and the reference is 49kW, the absolute deviation is 103.1kW - ​​49kW = 54.1kW; if the current voltage is 359.6V and the reference is 380V, the absolute deviation is 359.6V - 380V = -20.4V (the negative sign indicates that it is lower than the reference). The absolute deviation value is divided by the reference benchmark and expressed as a percentage. The relative deviation of power is approximately (54.1kW ÷ 49kW) × 100% ≈ 110.4%; the relative deviation of voltage is approximately (-20.4V ÷ 380V) × 100% ≈ -5.4%. The level is determined according to the location of the monitoring unit where the deviation value is located. The deviation is slight within the inner boundary, moderate between the inner and outer layers, and severe outside the outer layer. For example, 103.1kW is at the upper boundary of the power level and is judged as a severe positive deviation; 359.6V is at the lower boundary of the voltage level and is judged as a severe negative deviation.

[0038] Take the parameter values ​​of the three most recent consecutive time points in the trajectory, with an interval of 0.5 seconds and a total duration of 1 second, and calculate the change per unit time. For example, in the power trajectory, T2: 90kW, T2.5: 96kW, T3: 103.1kW, the instantaneous rate of change = (103.1kW - ​​90kW) ÷ 1 second = 13.1kW / second (a positive value indicates an upward trend). Count the time for continuous deviation from the same direction. For example, if the power continuously increases from T1.5 (86.9kW) to T3 (103.1kW) for 1.5 seconds, it is judged as a continuous positive trend. Based on the relative deviation and deviation level settings, the adjustment amount is 80% of the deviation degree when there is a serious deviation to ensure rapid correction, 50% for moderate deviation, and 20% for slight deviation. For example, if the power has a serious positive deviation (110.4%), the basic adjustment amount = 110.4% × 80% ≈ 88.3%, that is, 49kW × 88.3% ≈ 43.3kW, which needs to be reduced by 43.3kW.

[0039] Adjustments are made based on the instantaneous rate of change. The coefficient for an upward trend (positive rate of change) is 1.2, increasing the adjustment amount. The coefficient for a downward trend (negative rate of change) is 0.8, decreasing the adjustment amount. The instantaneous power rate of change is 13.1 kW / s, increasing. The corrected adjustment amount is 43.3 kW × 1.2 ≈ 52.0 kW. The adjustment amount is converted to a specific command value. For example, if the original power command is 103.1 kW, the corrected command is 103.1 kW - 52.0 kW = 51.1 kW. The voltage deviates significantly in the negative direction (-5.4%). The basic adjustment amount is 5.4% × 80% = 4.32%, with a reference voltage of 380 V × 4.32% ≈ 16.4 V. Because the voltage is trending downwards, assuming a rate of change of -2 V / s, and a correction coefficient of 1.2, the final adjustment amount is 16.4 V × 1.2 ≈ 19.7 V. The corrected voltage command is 359.6 V + 19.7 V ≈ 379.3 V (close to the reference voltage of 380 V).

[0040] By deploying monitoring units at different levels along the inner and outer boundaries of the microgrid, gradient early warning is achieved, allowing for the early detection of trends approaching anomalies and triggering emergency corrections. Compared to single-boundary monitoring, this approach also captures initial deviations through a central monitoring unit, reducing the probability of the system entering an abnormal state. Full-range data acquisition ensures trajectory integrity, avoiding the omission of key change points and making the assessment more comprehensive. Absolute deviation is used to quantify the degree of anomaly, avoiding subjective judgment. Deviation level classification matches the adjustment amount with the severity of the anomaly, preventing system oscillations caused by large adjustments for small deviations. Instantaneous change rate and continuous assessment make the adjustment more predictable, avoiding the lag caused by waiting for parameters to stabilize before adjusting. Combining the basic adjustment amount and trend correction coefficient makes the command both precise and flexible, avoiding over-adjustment and quickly returning to the normal range, thus improving the stability of microgrid parameters.

[0041] In a preferred embodiment of the present invention, monitoring the power communication status according to the control parameter correction instruction and generating a control transfer trigger signal when a communication anomaly is detected may include: In this embodiment of the invention, based on the control parameter correction command, the real-time change characteristics of power parameters and voltage parameters are extracted. Specifically, this includes: based on the obtained control parameter correction command, such as power correction command 51.1kW and voltage correction command 379.3V, firstly determining the type of real-time change characteristics to be extracted, including parameter change amplitude, change frequency, and change stability; selecting the real-time parameter values ​​at 5 consecutive time points after the correction command is issued, and comparing them with the correction command value. For example, the 5 real-time values ​​of the power parameter are 51.1kW, 50.8kW, 50.5kW, 50.3kW, and 50.1kW. The difference between each value and the correction command value of 51.1kW is 0kW, -0.3kW, -0.6kW, -0.8kW, and -1.0kW, respectively. The sum of the absolute values ​​of these differences (0+0.3+0.6+0.8+1.0=2.7kW) is then divided by the number of data points, 5, to obtain the average change amplitude of 0.54kW, reflecting the average magnitude of parameter fluctuations around the command value.

[0042] The number of times a parameter value exceeds the correction command value within one minute is counted. For example, if the voltage correction command is 379.3V, the real-time voltage exceeds this value 12 times and falls below it 8 times within one minute, for a total of 20 times, or a change frequency of 20 times / minute. This reflects the frequency of parameter fluctuations. The real-time parameter values ​​within one minute are arranged in chronological order, and the difference between adjacent values ​​is calculated. For example, the difference between 379.3V and 379.5V is 0.2V, and the difference between 379.5V and 379.2V is -0.3V, etc. The absolute values ​​of all differences are taken, summed, and then divided by the number of differences (59, since there are 60 data points per minute) to obtain the average fluctuation difference. For example, if the total sum of absolute values ​​is 11.8V, 11.8 ÷ 59 ≈ 0.2V. The smaller the value, the more stable the change. The calculation results of the three features are integrated to form a real-time change feature dataset of power and voltage parameters.

[0043] Based on real-time change characteristics, the communication link status of each AC / DC power supply unit is monitored in real time through the communication interface of the central controller. This includes communication delay, data packet transmission rate, and bit error rate. Specifically, starting from the communication interface of the central controller, for each AC / DC power supply unit (e.g., photovoltaic inverter, energy storage converter, etc., assuming a total of 5 units, numbered S1 to S5), the three indicators of communication delay, data packet transmission rate, and bit error rate are monitored respectively. The communication delay is calculated, and the central controller sends a timestamped measurement data to each power supply unit. Test data packets are sent once every 5 seconds, and the sending time is recorded, such as T1=10:00:00.000. After the power supply unit receives the packet, it immediately returns an acknowledgment packet. The central controller records the receiving time, such as T2=10:00:00.008. The communication delay = receiving time - sending time = 0.008 seconds. After 10 consecutive monitorings, the average of the 10 delay values ​​is taken, such as 0.008 seconds, 0.009 seconds...0.010 seconds, with a total of 0.085 seconds and an average value of 0.0085 seconds, which is taken as the current communication delay of the unit.

[0044] Calculate the data packet transmission rate by counting the total number of bytes of data packets successfully transmitted between the central controller and the power unit within one minute. Each data packet is fixed at 1024 bytes. Assuming 300 packets are transmitted within one minute, the total number of bytes = 300 × 1024 = 307200 bytes. The transmission rate = total number of bytes ÷ 60 seconds = 307200 ÷ 60 = 5120 bytes / second, which is converted to kbps (1 byte = 8 bits), i.e., 5120 × 8 ÷ 1024 = 40 kbps.

[0045] To calculate the bit error rate, in 300 data packets transmitted in 1 minute, each data packet contains 1024 bytes (8192 bits), and the total number of transmitted bits = 300 × 8192 = 2457600 bits. Error bits are identified by check codes. If 25 error bits are detected, the bit error rate = number of error bits ÷ total number of transmitted bits = 25 ÷ 2457600 ≈ 0.00001017, or approximately 0.001017%. For each power supply unit, S1 to S5 repeat the above calculation to obtain the communication link status data of each unit.

[0046] The communication link status is analyzed, and the overall channel status evaluation value is calculated. Communication anomalies are identified when communication latency exceeds a preset threshold, data packet transmission rate fails to meet transmission requirements, and bit error rate exceeds the allowable range. Specifically, the following steps are taken: First, set the judgment thresholds for each indicator: a preset threshold of 0.01 seconds for communication latency, a data packet transmission rate requirement of no less than 30 kbps, and an allowable bit error rate of no more than 0.001%. Then, calculate the overall channel status evaluation value, assigning weights to the three indicators: communication latency 40%, transmission rate 30%, and bit error rate 30%. Convert the actual value of each indicator into a score of 0-100, with higher scores indicating better status. For example, a unit with a communication latency of 0.0085 seconds (less than the threshold of 0.01 seconds) scores 80 points; a transmission rate of 40 kbps (more than 30 kbps) scores 9 points. 0 points; Bit error rate 0.001017%, slightly higher than 0.001%, 40 points, overall status evaluation value = 80×40%+90×30%+40×30%=32+27+12=71 points. When any one of the three indicators fails to meet the requirements, the evaluation value is combined for comprehensive judgment. For example, if the communication delay of a certain unit is 0.012 seconds, which is greater than the threshold of 0.01 seconds, even if the evaluation value is 65 points, it is still judged as a delay abnormality; if the transmission rate is 25kbps, which is lower than 30kbps, it is judged as a rate abnormality; if the bit error rate is 0.0015%, which is greater than 0.001%, it is judged as a bit error abnormality; if multiple indicators fail to meet the standards, such as a delay of 0.013 seconds and a bit error rate of 0.002%, it is judged as a comprehensive abnormality. All power supply units are judged one by one, and the abnormal units and corresponding abnormality types are recorded.

[0047] When a communication anomaly is detected, a control transfer trigger signal is generated, including the anomaly type and the identifier of the abnormal power unit. Specifically, based on the judgment result, it is determined whether it is a time delay anomaly, a rate anomaly, a bit error anomaly, or a comprehensive anomaly. For example, if the communication delay of unit S3 is 0.012 seconds (exceeding the threshold), and other indicators are normal, the anomaly type is marked as a time delay anomaly. The number of the abnormal unit, such as S3, is associated with the corresponding equipment type, such as a photovoltaic inverter, to form identification information, such as S3-photovoltaic inverter. The trigger signal contains three parts: a timestamp, such as 2025-08-27 10:05:30, the anomaly type, such as time delay anomaly, and the abnormal unit identifier, such as S3-photovoltaic inverter. At the same time, the severity of the anomaly is added, divided according to the evaluation value: above 60 points is mild, 40-60 points is moderate, and below 40 points is severe. For example, the evaluation value of S3 is 71 points, which is marked as a mild time delay anomaly. The above content is converted into a standardized signal format, and the finally generated control transfer trigger signal is sent to the backup control through the internal communication bus to complete the signal transmission.

[0048] By calculating the magnitude, frequency, and stability of parameter changes, the response of power and voltage parameters to correction commands can be captured, avoiding the disconnect between monitoring communication indicators and ignoring the actual control effect. This improves the foresight of anomaly warnings. Multi-dimensional monitoring of communication latency, transmission rate, and bit error rate can comprehensively reflect link quality. Compared with single indicator monitoring, multi-dimensional data can more accurately locate communication problems and provide detailed basis for anomaly analysis. Trigger signals include details such as timestamps, anomaly types, and unit identifiers, enabling backup controllers to quickly locate problems, take over control in a targeted manner, reduce system oscillations, ensure that the microgrid can still maintain stable operation during communication anomalies, reduce the risk of power outages caused by communication failures, and improve the system's fault tolerance and reliability.

[0049] In a preferred embodiment of the present invention, when a control transfer trigger signal is detected, a dominant power supply unit is elected according to a preset rule based on the real-time comparison results of the output current of each power supply unit, and a control switching command is generated, which may include: In this embodiment of the invention, a data acquisition process is initiated based on a control transfer trigger signal to acquire the output current measurement values ​​of all grid-connected power units in the microgrid in real time. Specifically, when the system detects a control transfer trigger signal, such as a fault signal of the currently dominant power unit or a load change signal, the data acquisition process is initiated. During this process, raw output current data of each power unit in the microgrid is collected using current sensors. A fixed acquisition time interval is set, for example, once every 0.01 seconds. Each acquisition is for a single power unit, and a preset number of acquisitions are performed, such as 10, to obtain multiple sets of raw measurement values ​​of the output current of that power unit. Then, each set of raw measurement values ​​is processed... The error correction calculation begins by first calculating the average error value in the data collected by the power unit. For example, it's the average difference between each measured value and the standard current value from the past 100 data collections. Then, the average error value is subtracted from the original measured value for each collection to obtain the corrected single measurement value. Next, the arithmetic mean of 10 corrected measurements for the same power unit is calculated by adding the 10 corrected values ​​together and dividing the sum by 10 to obtain the real-time measured value of the output current of the power unit. This completes the current data acquisition and processing for a single power unit. Following the same steps, data acquisition, error correction, and arithmetic mean calculation are performed sequentially for all grid-connected power units in the microgrid to finally obtain the real-time measured values ​​of the output current of all power units.

[0050] The output current measurements are compared and calculated to obtain the ranking of the output current magnitudes of each power supply unit. Specifically, this involves: selecting the first power supply unit's measured value from all real-time output current measurements of the grid-connected power supply units as the initial reference value; then, selecting the second power supply unit's measured value and comparing it with the initial reference value. If the second measured value is greater than the initial reference value, it is updated as the new reference value; if the second measured value is less than the initial reference value, the initial reference value remains unchanged; if they are equal, the initial reference value is used as the current reference value. Then, the third power supply unit's measured value is selected and compared with the current reference value again using the same comparison operation. The reference value is updated or maintained based on the comparison result. This process is repeated for each subsequent power supply unit's output current. The measured current value is compared with the current reference value until the measured values ​​of all power supply units have been compared. After all comparisons are completed, the position of each measured value during the comparison process is recorded. For example, after the reference value has been updated multiple times, the power supply unit corresponding to the final reference value is the unit with the largest output current, and its ranking position is recorded as 1. Then, the power supply unit corresponding to the largest current value is excluded, and the new reference value is determined again according to the above comparison steps based on the measured values ​​of the remaining power supply units. The corresponding power supply unit is the unit with the second largest output current, and its ranking position is recorded as 2. This operation of excluding the largest current value and re-comparing is repeated until the output current measured values ​​of all power supply units have determined their respective ranking positions in descending order, and finally the complete ranking result of the output current of each power supply unit is obtained.

[0051] Based on the sorting results and the preset unit election rules, the power supply unit that meets the rule requirements is selected as the dominant power supply unit from all power supply units. A control switching instruction including the dominant power supply unit's identification information is generated. Specifically, this includes: retrieving the preset unit election rules, for example, prioritizing the power supply unit with the largest output current and current fluctuation values ​​less than 5% in three consecutive measurements as the dominant power supply unit. The first step is to filter out the power supply unit at sorting position 1 (i.e., the one with the largest output current) based on the previously obtained output current sorting results. The real-time output current measurement values ​​of this power supply unit are then obtained for three consecutive measurements, assuming they are I1, I2, and I3. Then, the current fluctuation value of this power supply unit is calculated, first by calculating the difference between two adjacent measurements, i.e., |I2-I1| and |I2-I1|. I3-I2|; then calculate the percentage of these two differences to the previous measurement value, i.e. (|I2-I1| / I1)×100% and (|I3-I2| / I2)×100% respectively; then determine whether both percentages are less than 5%: if both percentages are less than 5%, the power supply unit meets the preset rule requirements and is selected as a candidate dominant power supply unit; if either percentage is greater than or equal to 5%, the power supply unit is excluded, and the power supply unit with the second largest output current at the second sorting position is selected. The current fluctuation value of its three consecutive acquisitions is calculated in the same way, and it is determined whether it is less than 5%. If the power supply unit at position 2 still does not meet the requirements, continue to select the power supply unit at position 3 and repeat the above current fluctuation value calculation and judgment steps until the first power supply unit that meets the rule of being ranked high in output current and having a current fluctuation value of less than 5% for 3 consecutive times is found. This power supply unit is then officially determined as the dominant power supply unit. After determining the dominant power supply unit, the unique identification information of the power supply unit, such as the unit number and device code, is retrieved from the system database. The identification information is then associated and integrated with the instruction content for switching control to this unit to generate a complete control switching instruction. The instruction explicitly includes the identification information of the dominant power supply unit.

[0052] By setting a fixed acquisition time interval and continuously acquiring multiple sets of raw data, and then performing error correction and arithmetic averaging, the measurement error caused by factors such as the accuracy deviation of the current sensor and external electromagnetic interference during a single acquisition is reduced. This makes the real-time measured value of the power unit output current closer to the true current value, avoiding the deviation of the selection result due to data error and ensuring the accuracy of microgrid power control. Combined with the preset rules for output current sorting and current fluctuation value judgment, it can not only select the power unit with strong output capability as the dominant unit, but also eliminate the power unit with unstable current by calculating the current fluctuation value, ensuring that the dominant unit can continuously and stably supply power and reducing the microgrid power interruption or voltage fluctuation problem caused by the instability of the power unit.

[0053] In a preferred embodiment of the present invention, in response to a control switching command, the dynamic response characteristics of the AC / DC power supply are analyzed in real time, and a damping compensation control signal is generated when oscillation characteristics are identified. This may include: In this embodiment of the invention, based on the control switching command, a real-time monitoring process is initiated to collect dynamic response data of the output power and output voltage of each AC / DC power supply unit. Specifically, this includes: setting a threshold for the trigger condition of monitoring initiation. This threshold is a numerical range determined in advance based on the stable range of the control signal during normal operation of the AC / DC power supply system. When the control switching command is received, the control signal parameters in the command are extracted, and the parameters are compared and calculated with the set threshold. If the parameters exceed the stable range, it is determined that the monitoring initiation condition is met, and the real-time monitoring process is initiated; if they are within the stable range, monitoring is not initiated.

[0054] All power supply units in the entire AC / DC power supply system are pre-numbered and registered, establishing a correspondence table between unit numbers and unit attributes, including DC power supply units, AC power supply units, unit rated power, and unit installation location. After monitoring starts, based on the system topology, this correspondence table is traversed to calculate the degree of association between each power supply unit and the control switching command. The degree of association is calculated using the unit's priority coefficient in the system power supply path. The priority coefficient is pre-set based on the unit's impact on the system's power supply stability; the greater the impact, the higher the coefficient. Power supply units with priority coefficients greater than the set screening threshold are selected as the AC / DC power supply units for which data needs to be collected. For each selected power supply unit... The power unit is equipped with a power acquisition sensor. The sensor acquires the current and voltage signals at the unit's output in real time. For AC power units, the acquired current and voltage are instantaneous values, and the average value over one cycle needs to be calculated. This is done by integration over one cycle. For example, for a 50Hz AC power cycle, the sum of the products of the instantaneous current and voltage values ​​within 0.02 seconds is used, and then divided by the cycle length to obtain the average output power over that cycle. For DC power units, the instantaneous current value and instantaneous voltage value are directly multiplied to obtain the real-time DC output power. To ensure data accuracy, the instantaneous value is acquired and the power is calculated every 0.01 seconds. After 10 consecutive acquisitions, the average value is taken as the output power data at that moment. Similarly, each power supply unit is equipped with a voltage acquisition device, with a sampling frequency set to 1kHz, meaning 1000 voltage values ​​are collected per second. After monitoring is started, timing begins from the instant the control switch command is issued, and the voltage values ​​at the output terminals of each power supply unit are continuously collected at 0.001-second intervals. For AC voltage, the collected instantaneous values ​​are used, and their effective values ​​need to be calculated. This is done by integrating the square of the instantaneous voltage value within one cycle, dividing by the cycle length, and then taking the square root to obtain the effective value of the AC voltage. For DC voltage, the collected instantaneous values ​​are directly recorded, and the average value is calculated every 10 instantaneous values ​​collected as the DC voltage dynamic response data for that time period. At the same time, the acquisition time point corresponding to each data point is recorded to form a dynamic response dataset of voltage changes over time.

[0055] Time-domain waveform analysis is performed on the dynamic response data to detect the presence of power oscillation characteristics. Specifically, this involves establishing a Cartesian coordinate system with time as the x-axis and power value as the y-axis for the collected output power and voltage data of each power unit. Based on the time point and value corresponding to each data point, the corresponding coordinate points are marked in the coordinate system. Then, adjacent coordinate points are connected sequentially with straight lines according to the chronological order to form a continuous time-domain waveform trend. During the construction process, if the difference between an individual data point and its adjacent data points exceeds a set abnormal threshold (set as ±20% of the average of the five data points before and after the data point), the data point is determined to be abnormal. The abnormal data point is then replaced with the average of the two adjacent normal data points to ensure the continuity and accuracy of the waveform. In the constructed power time-domain waveform, a continuous time period is selected, with the duration set to 5 seconds after the control handover command is issued. This is because the dynamic response during the handover process typically stabilizes within 5 seconds. Within this time period, the maximum and minimum values ​​of the power waveform are identified, and the difference between the maximum and minimum values ​​is calculated to obtain the power fluctuation amplitude. Simultaneously, the average power value within this time period is calculated. All power data within this time period are summed, and the result is divided by the number of data points. The fluctuation amplitude is then divided by the average value to obtain the relative fluctuation amplitude. The relative fluctuation amplitude is one of the important indicators for determining whether oscillation occurs. Observe adjacent two... A peak is a local maximum value in the waveform, where the value at that point is greater than the values ​​of the two adjacent data points before and after it, or a trough is a local minimum value in the waveform, where the value at that point is less than the time interval between the values ​​of the two adjacent data points before and after it. Five consecutive sets of adjacent peaks or troughs are selected, and the time interval for each set is calculated. Then, these five time intervals are added together and divided by 5 to obtain the average fluctuation period. Within the above 5-second time period, the number of peaks or troughs in the power waveform is counted. If the number of peaks and troughs is inconsistent, the one with the larger number is used to obtain the number of power fluctuations within that time period. The preset oscillation judgment criteria include a relative fluctuation amplitude threshold set at 30%, meaning that a relative fluctuation amplitude exceeding 30% indicates potential oscillation characteristics; an average fluctuation period threshold set at 0.5 to 5 seconds, indicating that the fluctuation has a certain regularity and meets the characteristics of an oscillation period; and a fluctuation frequency threshold set at 3 times, meaning that more than 3 fluctuations within 5 seconds indicate frequent fluctuations and meet the characteristics of continuous oscillation. The calculated relative fluctuation amplitude, average fluctuation period, and fluctuation frequency are compared with their corresponding judgment thresholds. If all three indicators meet the threshold requirements (relative fluctuation amplitude > 30%, 0.5 seconds ≤ average fluctuation period ≤ 5 seconds, and fluctuation frequency > 3 times), then power oscillation characteristics are determined to exist; if any one indicator does not meet the threshold requirements, then power oscillation characteristics are determined not to exist.

[0056] When an oscillation characteristic is identified, a corresponding damping compensation control signal is calculated and generated based on the amplitude and frequency information of the oscillation characteristic. Specifically, this includes: determining the duration of the oscillation in the power time-domain waveform with the identified oscillation characteristic, from the first peak to the last peak and when the subsequent waveform fluctuation amplitude is less than 10% of the amplitude; within this time period, identifying all peak and trough values ​​one by one, calculating the difference between each peak and the adjacent trough, i.e., the amplitude within a single oscillation cycle; summing the amplitudes within all single oscillation cycles and dividing by the number of oscillation cycles to obtain the average amplitude of the oscillation characteristic; simultaneously, identifying the maximum amplitude among all single oscillation cycles as the maximum amplitude of the oscillation characteristic, with subsequent calculations primarily based on the average amplitude, and the maximum amplitude used for verification. Based on the previously calculated average fluctuation period (denoted as T), the oscillation frequency f is calculated according to the reciprocal relationship between frequency and period, i.e., f = 1 / T. To improve the accuracy of frequency calculation, 10 consecutive oscillation periods within the oscillation duration are selected, and the duration of each period is calculated. The average duration of these 10 periods is then calculated as the final average fluctuation period T. Substitute this into the frequency calculation formula to obtain the accurate oscillation frequency f. A pre-established correspondence mechanism between oscillation amplitude and damping compensation amplitude is established. The core principle is that the damping compensation amplitude and oscillation amplitude are positively correlated. Simultaneously, the system impedance characteristics are considered. The system impedance value R is pre-obtained through system parameter measurements. The measurement method involves applying a known voltage to the system under no-load conditions, measuring the current, and calculating the impedance using Ohm's law R=U / I. The specific calculation formula is: Damping compensation control signal amplitude = (average oscillation amplitude × system impedance correction coefficient) / system safety factor. The system impedance correction coefficient is determined based on the system impedance value R. When R is between 10Ω and 20Ω, the correction coefficient is 0.8; when R is greater than 20Ω, the correction coefficient is 0.6; and when R is less than 10Ω, the correction coefficient is 1.0. The system safety factor is set to 1.2 to avoid over-compensation leading to new system fluctuations. For example, if the average oscillation amplitude is 50W and the system impedance R is 15Ω, corresponding to a correction coefficient of 0.8, then the damping compensation control signal amplitude = (50 × 0.8) / 1.2 ≈ 33.33W, corresponding to the voltage or current amplitude. The frequency of the damping compensation control signal must be consistent with the oscillation frequency to achieve accurate oscillation cancellation. Therefore, the calculated oscillation frequency f is directly used as the frequency of the damping compensation control signal. Simultaneously, to ensure that the compensation signal and the oscillation signal are out of phase, the phase difference needs to be calculated. By comparing the phases of the oscillation waveform and the compensation signal waveform, it is ensured that the phase of the compensation signal lags behind the oscillation signal by 180°. This is specifically achieved by setting a phase offset parameter during signal generation. The phase offset is calculated as: Phase offset = Initial phase of oscillation signal + 180°. Based on the calculated amplitude, frequency, and phase offset of the damping compensation control signal, the waveform type of the control signal is determined. Since the oscillations of AC / DC power systems are mostly sinusoidal or approximately sinusoidal fluctuations, the damping compensation control signal adopts a sinusoidal waveform. Using time t as a variable, the control signal waveform data is generated according to the variation law of the sine function. The control signal value corresponding to each time point t is: Control signal value = Damping compensation control signal amplitude × sin(2πft). +phase offset), where the interval of t is consistent with the previous data sampling interval. During the entire period of oscillation, the control signal value at each time point is calculated point by point according to the formula to form continuous damping compensation control signal waveform data. The generated control signal waveform data is a digital quantity, which needs to be converted into an analog signal before it can be sent to the power control unit. During the conversion process, the output range of the analog signal is first determined. According to the input requirements of the power control unit, it is set to 0V to 5V. The conversion coefficient between digital and analog quantities is calculated. The conversion coefficient = (maximum analog output value - minimum analog output value) / (maximum digital value - minimum digital value). Assuming that the digital quantity range is 0 to 4095 (12-bit AD conversion), the conversion coefficient = 5V / 4095 ≈ 0.00122V / unit. Then, the digital value of the control signal at each time point is multiplied by the conversion coefficient to obtain the corresponding analog voltage value. The analog voltage value is then output through the D / A conversion mechanism to form the final damping compensation control signal, which is sent to the control terminal of each AC / DC power supply unit to realize damping compensation control.

[0057] By identifying and replacing abnormal data points, and by accurately calculating the effective values ​​of AC power and voltage, data deviations caused by accidental interference or sensor errors are reduced. This ensures that the collected output power and voltage dynamic response data can truly reflect the actual operating status of the AC / DC power supply during control switching. By calculating the correlation between each power unit and the control switching command, the total amount of data collected is reduced, lowering the load on sensors, data transmission channels, and data processing modules, avoiding waste of system resources, and improving data processing speed to ensure the real-time nature of the monitoring process. By constructing a complete time-domain waveform and setting clear judgment thresholds from three dimensions—fluctuation amplitude, period, and frequency—a multi-indicator comprehensive judgment system is formed, rather than a single-indicator judgment. This multi-dimensional analysis method can effectively distinguish between normal dynamic fluctuations and harmful power oscillations, avoiding misjudging normal fluctuations as oscillations leading to unnecessary compensation, or failing to identify potential oscillations due to the omission of a single indicator, thus ensuring the accuracy of oscillation characteristic detection. like Figure 2 As shown, in a preferred embodiment of the present invention, based on the damping compensation control signal, monitoring the actual operating conditions of the microgrid and dynamically adjusting the power control parameters to achieve the final power allocation may include: In this embodiment of the invention, the central controller generates adjustment instructions for the power output reference values ​​of each power unit based on the damping compensation control signal. Specifically, the central controller first obtains the initial power output reference values ​​of each power unit. These initial reference values ​​are usually determined based on the microgrid's design capacity, the rated power of each power unit, and the preset power allocation ratio. For example, if there are two power units in the microgrid with rated powers of 100kW and 200kW respectively, and the power is preset to be allocated in a 1:2 ratio, the initial reference values ​​are 50kW and 100kW respectively when the total load power is expected to be 150kW. The central controller receives the damping compensation control signal, which contains information related to the compensation amount used to offset power fluctuations in the microgrid operation and maintain system stability. The controller first analyzes the strength and direction of the damping compensation control signal to determine whether there is a power oscillation or instability trend in the current microgrid. Assuming that the damping compensation control signal indicates that the system damping needs to be increased to suppress power fluctuations, the controller calculates the adjustment range of the power output reference values ​​of each power unit. When calculating the adjustment range, a damping compensation coefficient is taken into account. This coefficient is preset based on the microgrid topology, component parameters, etc. For example, if the damping compensation coefficient is 0.2 and the initial reference value is 50kW for a power supply unit, the amount that needs to be adjusted due to damping compensation is 50×0.2=10kW. If the current power of the system is decreasing, the output of the power supply unit needs to be increased, and the adjusted reference value is 50+10=60kW; if it is increasing, the output needs to be reduced, and the adjustment is 50-10=40kW. Following the same logic, such calculations are performed for each other power supply unit, and finally, their respective power output reference value adjustment commands are generated.

[0058] The microgrid monitoring device collects bus voltage, frequency, and total load power data in real time according to adjustment commands to obtain the actual operating conditions of the microgrid. Specifically, after receiving the adjustment command, the microgrid monitoring device will start a high-frequency data acquisition mode. The acquisition frequency is usually set according to the dynamic response requirements of the microgrid, such as 50-100 times per second. For bus voltage data acquisition, the monitoring device will obtain the instantaneous voltage values ​​of each monitoring point on the bus through voltage sensors. Then, it will process the acquired instantaneous voltage values ​​to calculate the effective value of the voltage. The specific process is as follows: first, each instantaneous voltage value is squared; then, the squared values ​​are averaged over a certain time interval, such as one AC cycle (0.02 seconds in my country); finally, the square root of the average value is taken to obtain the effective value of the bus voltage during that time period, which is used as the real-time bus voltage data. Regarding bus frequency data acquisition, the monitoring device captures the zero-crossing points of the voltage signal through a frequency measurement mechanism, calculates the time interval between two adjacent positive zero-crossing points (this time interval is the AC cycle), and then calculates the bus frequency based on the reciprocal relationship between frequency and cycle (frequency = 1 / cycle). For example, if the time interval between two adjacent positive zero-crossing points is 0.02 seconds, then the frequency is 1 / 0.02 = 50Hz. To improve accuracy, multiple cycles are measured continuously, the average value of the cycles is calculated, and then substituted into the formula to obtain the average frequency, which serves as the real-time bus frequency data. For total load power data acquisition, the monitoring device... The system collects real-time current values ​​from the bus via current sensors. Combined with previously obtained bus voltage RMS values, and based on the power calculation formula (active power = voltage RMS value × current RMS value × power factor), it first obtains the current power factor through a power factor measurement module. Then, it multiplies the voltage RMS value, current RMS value, and power factor to obtain the instantaneous total load active power. Similarly, it averages the instantaneous active power over a certain period to obtain real-time total load power data. By integrating the collected and processed bus voltage, frequency, and total load power data, the actual operating condition data of the microgrid is obtained.

[0059] The central controller utilizes actual operating condition data and a parameter adaptive adjustment mechanism to dynamically calculate and update the droop coefficient and power limit parameters of each power supply unit. Specifically, this includes: firstly, processing the dynamic calculation and updating of the droop coefficient, which reflects the relationship between the output power change of the power supply unit and the voltage or frequency change. It is usually divided into voltage droop coefficient and frequency droop coefficient. Taking the frequency droop coefficient as an example, the central controller first sets an ideal frequency range, such as 49.5-50.5Hz in my country's microgrids, and the corresponding power output range, from the minimum output power to the maximum output power of each power supply unit. Based on the bus frequency in the actual operating condition data, it determines whether the current frequency deviates from the ideal range. Assuming the ideal frequency is 50Hz, and the power output range of a certain power supply unit is 20-100kW, if the actual frequency is 50.2Hz, which is higher than the ideal frequency, it indicates that the system may have excess power, and the output power of that power supply unit needs to be reduced.

[0060] When calculating the frequency droop factor, first determine the frequency deviation value (actual frequency - ideal frequency), i.e., 50.2 - 50 = 0.2Hz. Then, based on the preset frequency droop characteristics, determine the power adjustment ratio corresponding to each 1Hz deviation. For example, if it is set that for every 1Hz increase in frequency, the power output of the power supply unit needs to be reduced by 10% of its rated power, and the rated power of the power supply unit is 100kW, then for every 1Hz increase, the power decreases by 10kW. Therefore, for a deviation of 0.2Hz, the power needs to be reduced by 10 × 0.2 = 2kW. At this time, according to the definition of the droop factor (droop factor = power change / frequency change), the current frequency droop factor is 2kW / 0.2Hz = 10kW / Hz. If the actual frequency is lower than the ideal frequency, the calculation logic is similar, except that the power adjustment direction is to increase, and finally the corresponding frequency droop factor is obtained. The calculation process for the voltage droop coefficient is similar to that for the frequency droop coefficient. Using an ideal voltage range, such as 380V ± 5%, as a benchmark, the power adjustment is calculated based on the deviation between the actual bus voltage and the ideal voltage, combined with preset voltage droop characteristics and the power adjustment ratio corresponding to each 1V deviation. Then, according to the formula droop coefficient = power change / voltage change, the voltage droop coefficient is obtained. The central controller integrates the voltage droop coefficient and the frequency droop coefficient, combined with the current operating status of each power supply unit, such as remaining capacity and losses, to correct the initial droop coefficient, thus completing the dynamic update of the droop coefficient. Regarding the dynamic calculation and update of power limit parameters, the power limit includes an upper power limit and a lower power limit. The central controller calculates these based on the total load power in the actual operating data and the real-time status of each power supply unit, such as the remaining battery charge and the maximum output power corresponding to the photovoltaic cell's light intensity. Taking a battery power unit as an example, if the battery currently has 80% remaining charge, according to the battery's charging and discharging characteristics, it can output its maximum rated power when the remaining charge is above 70%. If the remaining charge is below 30%, the output power must be limited to below 50% of the rated power as the lower limit. Assuming the battery's rated power is 50kW and the current remaining charge is 80%, its upper limit power can be set to 50kW. Simultaneously, considering the total load power, if the total load power is low, the lower limit power will be appropriately increased to avoid over-discharge of the battery. For example, if the total load power is 3... If the system has 3 power supply units and the battery is required to handle 10kW according to the proportional allocation, then its lower limit power is set to 10kW to ensure that its output is not lower than this value to maintain the power balance of the system. For photovoltaic power supply units, the maximum output power that can be achieved at present is calculated based on real-time light intensity data and the correspondence between light intensity and output power, which is used as its upper limit power. The lower limit power is set according to the minimum operating requirements of the system, such as 5kW, to avoid the system being unstable due to excessively low output. Through such calculations, the power limit parameters of each power supply unit are dynamically updated.

[0061] Each power unit's local controller adjusts its power output based on the droop coefficient and power limit parameters to distribute load power to each power unit according to a preset ratio. Specifically, each power unit's local controller first receives the updated droop coefficient from the central controller, including the voltage droop coefficient, frequency droop coefficient, and power limit parameters (upper and lower power limits). The local controller then calculates the required power output adjustment for that power unit based on the droop coefficient and the microgrid's real-time voltage and frequency changes. For example, if the frequency droop coefficient is 10kW / Hz and the real-time frequency is 0.1Hz lower than the ideal frequency, according to the formula: Power Change = Droop Coefficient × Frequency Deviation (where the frequency deviation is the ideal frequency - actual frequency; because the actual frequency is lower, power output needs to be increased), then the power change = 10 × 0.1 = 1kW / Hz. W means that the power unit needs to increase its power output by 1kW. The local controller will calculate the adjusted target power output value based on the current power output value. Assuming the current power output value is 20kW, then the target power output value is 20+1=21kW. Then, the target power output value is compared with the power limit parameter. If the target power output value is higher than the upper limit power, the actual output power is adjusted to the upper limit power; if it is lower than the lower limit power, it is adjusted to the lower limit power; if it is within the limit range, it is adjusted according to the target power output value. For example, if the upper limit power of a power unit is 30kW and the lower limit power is 8kW, and the calculated target power output value is 21kW, which is within the range of 8-30kW, then the local controller will send a command to the power regulation component (such as the inverter) of the power unit to adjust the power output to 21kW. The local controller monitors the adjusted power output in real time, comparing the actual output power of the power supply unit with the load power it should bear according to the preset ratio. Assuming the preset ratio is 20% of the total load power borne by the power supply unit, and the current total load power is 100kW, the unit should bear 20kW. If the actual adjusted output power is 21kW, slightly higher than the preset ratio, the local controller will fine-tune it again based on the droop coefficient, calculating the power change. For example, based on the voltage droop coefficient, if the current voltage is slightly higher than the ideal voltage, the power output can be appropriately reduced. Assuming the voltage droop coefficient is 5kW / V and the voltage deviation is 0.2V (actual voltage - ideal voltage), the power change would be 5 × 0.2 = 1kW, adjusting the actual output power from 21kW to 20kW to conform to the preset ratio. Through this repeated adjustment, it ensures that each power supply unit distributes load power according to the preset ratio.

[0062] By combining damping compensation control signals to generate adjustment commands, potential power fluctuations and system instability issues in microgrids can be addressed in advance. The damping compensation control signal reflects the dynamic characteristics of the system. Adjusting the power output reference values ​​of each power unit based on this signal allows the power unit's output to adapt to system changes in advance, preventing the amplification of power oscillations. Real-time and accurate bus voltage, frequency, and total load power data are the foundation for refined control of microgrids. The effective voltage value, average frequency, and average total load power data obtained through high-frequency acquisition and processing can reflect the actual operating status of the microgrid in a timely manner. When the microgrid experiences voltage anomalies, frequency deviations from the standard range, or sudden changes in total load power, the monitoring device can quickly capture these changes, providing timely basis for the central controller's decision-making, avoiding untimely control due to data lag, and reducing the risk of equipment damage and system failure. In addition, complete operating condition data can provide an accurate calculation basis for parameter adjustment and power allocation, ensuring that the implementation of various control strategies is based on the real system state, improving the accuracy and reliability of control, and providing data support for microgrid operation optimization, fault diagnosis, and maintenance.

[0063] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0064] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0065] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An adaptive control system for AC / DC power supply in a microgrid, characterized in that, include: The data acquisition module is used to collect the operating parameters of AC / DC power supply in real time through local sensors and generate raw operating data including voltage, current, frequency and power information. The instruction generation module is used to generate initial power allocation instructions based on the original operating data and through a preset droop characteristic calculation strategy. The evaluation and adjustment module is used to extract the time-series characteristics of power and voltage command values ​​over time based on the initial power allocation command, obtaining the dynamic change sequences of power and voltage. Based on these dynamic change sequences, statistical benchmark values ​​are calculated for a given period to establish power and voltage reference benchmarks. Based on these benchmarks and considering the operating constraints of AC / DC power supplies in the microgrid, allowable positive and negative deviation thresholds for power and voltage are set to determine the allowable deviation range. Based on these thresholds, the positive and negative deviation evaluation directions for power and voltage relative to the reference benchmarks are determined. Using the power and voltage reference benchmarks as centers and the allowable deviation ranges as boundaries, dynamic power and voltage intervals are constructed for real-time status determination. Monitoring units are deployed at the inner and outer boundaries of these intervals. The system forms a multi-layer monitoring structure. Utilizing this structure, power and voltage parameters are collected in real time, and their time-series characteristics are acquired to generate operational status assessment trajectories for power and voltage. Based on these trajectories, the deviation and trend of the reference benchmark are analyzed, and the required adaptive adjustment is calculated to obtain control parameter correction commands. Specifically, based on the initial power allocation command, time-series data is extracted over a 10-minute timeframe with a 10-second sampling interval. An extreme value-weighted average is used, with higher weight for recent data, to dynamically calculate statistical benchmark values ​​for power and voltage. Combined with the actual operational constraints of the AC / DC power supply, including maximum and minimum power, voltage fluctuation range, and safety margin, positive and negative deviation thresholds are independently set to form a dynamic power and voltage judgment interval that updates over time. This avoids the limitations of fixed thresholds, allowing the benchmark and interval to adaptively adjust with changes in system status. Ten monitoring units are arranged in layers at the inner boundary, outer boundary, and center of the dynamic range, forming a double-layer early warning structure. Through continuous high-frequency acquisition, with a sampling frequency of once every 0.5 seconds, all parameter points are collected, generating a continuous evaluation trajectory corresponding to time and parameter values. This allows for early detection of deviation trends and capture of initial changes, reducing the probability of anomalies and ensuring the integrity and traceability of the trajectory. Based on the evaluation trajectory, the absolute and relative deviations of the current parameters from the benchmark are quantified. Different adjustment coefficients are assigned according to the level of deviation, including slight, moderate, and severe levels, corresponding to 20%, 50%, and 80%, respectively. At the same time, instantaneous change rate and trend persistence analysis are introduced to dynamically correct the adjustment amount. The amplification coefficient is 1.2 times when there is an upward trend, and the reduction coefficient is 0.8 times when there is a downward trend. Finally, control parameter correction commands are generated to enable power and voltage to quickly and smoothly return to the normal range, avoiding over-adjustment and system oscillation. The monitoring and triggering module is used to monitor the power communication status according to the control parameter correction command, and generate a control transfer trigger signal when a communication abnormality is detected. The election and switching module is used to elect a dominant power supply unit according to preset rules based on the real-time comparison results of the output current of each power supply unit when a control transfer trigger signal is detected, and to generate a control switching command. The analysis and compensation module is used to analyze the dynamic response characteristics of AC and DC power supplies in real time in response to control switching commands, and generate a damping compensation control signal when oscillation characteristics are identified. The parameter adjustment module is used to monitor the actual operating conditions of the microgrid and dynamically adjust the power control parameters based on the damping compensation control signal to achieve the final power distribution.

2. The adaptive control system for AC / DC power supply in a microgrid according to claim 1, characterized in that, Based on the raw operating data, an initial power allocation command is generated using a preset droop characteristic calculation strategy, including: Acquire the raw operating data of each AC / DC power supply unit in the microgrid, including actual voltage and actual frequency values; The actual voltage value and the actual frequency value are compared with the preset voltage reference value and frequency reference value, respectively, to obtain the voltage deviation value and the frequency deviation value; Based on the voltage deviation and frequency deviation values, calculate the active power deviation and reactive power deviation values ​​corresponding to each power supply unit. The active power deviation value and reactive power deviation value are input into the preset active frequency droop characteristic relationship and reactive voltage droop characteristic relationship of each power supply unit, and the initial active power command value and initial reactive power command value of each unit are calculated and generated respectively. The initial active power command value and initial reactive power command value of all power supply units are integrated to generate the initial power allocation command of the microgrid.

3. The adaptive control system for AC / DC power supply in a microgrid according to claim 2, characterized in that, Based on the control parameter correction instructions, the power communication status is monitored, and a control transfer trigger signal is generated when a communication anomaly is detected, including: Based on the control parameter correction command, the real-time change characteristics of power parameters and voltage parameters are extracted; Based on real-time change characteristics, the communication link status of each AC / DC power supply unit is monitored in real time through the communication interface of the central controller, including communication latency, data packet transmission rate and bit error rate. The communication link status is analyzed and the overall status evaluation value of the current channel is calculated. When the communication delay is greater than the preset threshold, the data packet transmission rate does not meet the transmission requirements, and the bit error rate is greater than the allowable range, it is judged as a communication anomaly. When a communication anomaly is detected, a control transfer trigger signal is generated, which includes the anomaly type and the identifier of the abnormal power supply unit.

4. The adaptive control system for AC / DC power supply in a microgrid according to claim 3, characterized in that, When a control transfer trigger signal is detected, based on the real-time comparison results of the output current of each power supply unit, a dominant power supply unit is elected according to preset rules, and a control transfer command is generated, including: Based on the control transfer trigger signal, the data acquisition process is started to obtain the output current measurement values ​​of all grid-connected power supply units in the microgrid in real time. The output current measurements are compared and calculated to obtain the ranking of the output current of each power supply unit. Based on the sorting results and the preset unit election rules, the power supply unit that meets the rule requirements is selected from all power supply units as the dominant power supply unit, and a control switching instruction including the dominant power supply unit identification information is generated.

5. The adaptive control system for AC / DC power supply in a microgrid according to claim 4, characterized in that, In response to control switching commands, the dynamic response characteristics of the AC / DC power supply are analyzed in real time. When oscillation characteristics are detected, a damping compensation control signal is generated, including: Based on the control switching command, the real-time monitoring process is initiated to collect dynamic response data of output power and output voltage of each AC / DC power supply unit. Time-domain waveform analysis is performed on the dynamic response data to detect the presence of power oscillation characteristics; When oscillation characteristics are identified, the corresponding damping compensation control signal is calculated and generated based on the amplitude and frequency information of the oscillation characteristics.

6. The adaptive control system for AC / DC power supply in a microgrid according to claim 5, characterized in that, Based on the damping compensation control signal, the actual operating conditions of the microgrid are monitored and the power control parameters are dynamically adjusted to achieve the final power distribution, including: The central controller generates adjustment instructions for the power output reference values ​​of each power supply unit based on the damping compensation control signal; The microgrid monitoring device collects bus voltage, frequency and total load power data in real time according to the adjustment command to obtain the actual operating condition data of the microgrid; The central controller uses actual operating condition data and a parameter adaptive adjustment mechanism to dynamically calculate and update the droop coefficient and power limit parameters of each power supply unit. The local controller of each power supply unit adjusts the power output according to the droop coefficient and power limit parameters, so as to distribute the load power to each power supply unit according to a preset ratio.

7. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the system as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the system as described in any one of claims 1 to 6.

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