Power distribution cabinet multi-loop power adaptive distribution method and system

Abstract

The invention relates to the technical field of intelligent power distribution, and discloses a power distribution cabinet multi-loop power adaptive distribution method and system. The method comprises the following steps: synchronously acquiring current values of all loops at a fixed sampling period, and storing the current values into a loop current time sequence matrix; carrying out second-order difference operation on the matrix, and carrying out quotient on the obtained load change acceleration and a rated margin to obtain a load inertia coefficient; screening a high-risk loop set under the condition that the load inertia coefficient continuously exceeds a pre-judgment threshold value; and taking a weighted difference value of a rated margin rate and the load inertia coefficient as a future stability score, switching a part of loads in the high-risk loop set to a receiving loop with the highest score, and correcting the pre-judgment threshold value with a historical switching pre-judgment accuracy rate. According to the invention, the feed-forward pre-judgment capability of the multi-loop power distribution of the power distribution cabinet and the long-term stability of the switching decision are improved.

Description

Multi-circuit adaptive power distribution method and system for power distribution cabinets Technical Field

[0001] This application relates to the field of intelligent power distribution technology, and in particular to a method and system for adaptive power allocation of multiple circuits in a power distribution cabinet. Background Technology

[0002] Distribution cabinets are core equipment in industrial and civil power distribution systems, responsible for distributing electrical energy from the input bus to various output circuits, each supplying power to different loads. Traditional multi-circuit power distribution in distribution cabinets employs a static, fixed allocation strategy. The rated capacity of each circuit remains unchanged after being determined during the design phase, and each circuit operates independently, with overload protection provided by its own circuit breaker. This static allocation method can operate normally under long-term stable load conditions and is a conventional technique in this field.

[0003] However, in industrial production scenarios, the actual load of each output circuit fluctuates dynamically with changes in production conditions. Some circuits experience a continuous increase in load rate during peak production periods, while others remain under light load, leading to a severe imbalance in load distribution among the circuits. While existing technologies have improved solutions that collect current data from each circuit in real time and trigger load switching when the current exceeds a preset threshold, these solutions are essentially passive response mechanisms. Switching is only initiated when an overload has occurred or is about to trigger the circuit breaker, resulting in an inherent lag in the switching response and an inability to proactively intervene before an overload occurs. Furthermore, existing solutions select the receiving circuit based solely on its lightest current load, without considering the receiving circuit's own load variation trend. This carries the risk of transferring load from a high-risk circuit to another circuit whose own load is also rapidly increasing, potentially leading to cascading overload failures. Summary of the Invention

[0004] This application provides a method and system for adaptive power allocation of multiple circuits in a power distribution cabinet, which solves the problems of response lag caused by passive threshold triggering and cascading overload caused by lack of trend prediction in the selection of receiving circuits in the existing power allocation schemes for multiple circuits in power distribution cabinets. It improves the feedforward prediction capability and long-term stability of switching decisions in the power allocation of multiple circuits in power distribution cabinets.

[0005] In a first aspect, this application provides a method for adaptive power allocation across multiple circuits in a power distribution cabinet. The method includes: Step S1: Synchronously collecting real-time current values ​​of each output circuit of the power distribution cabinet at a fixed sampling period, and storing the current values ​​of each circuit at consecutive M time points in a rolling update manner into an N-row × M-column circuit current time-series matrix; Step S2: Performing a second-order difference operation on the time-series data of each row of the circuit current time-series matrix to obtain the load change acceleration of each circuit; quotienting the load change acceleration with the rated margin of each circuit to obtain the load inertia coefficient of each circuit; Step S3: Selecting a set of high-risk circuits from each output circuit based on the condition that the load inertia coefficient continuously exceeds a predicted threshold within K consecutive sampling periods; Step S4: Using the weighted difference between the rated margin rate of each candidate receiving circuit and the load inertia coefficient as a future stability score, switching some loads in the high-risk circuit set to the receiving circuit with the highest future stability score; and correcting the predicted threshold and the K value based on the historical switching prediction accuracy.

[0006] Secondly, this application provides a multi-circuit power adaptive allocation system for a power distribution cabinet. The system includes: an extraction module, used to synchronously collect real-time current values ​​of each output circuit of the power distribution cabinet at a fixed sampling period, and store the current values ​​of each circuit at consecutive M time points in a rolling update manner into an N-row × M-column circuit current time-series matrix; a calculation module, used to perform second-order difference operations on the time-series data of each row of the circuit current time-series matrix to obtain the load change acceleration of each circuit; and to divide the load change acceleration by the rated margin of each circuit to obtain the load inertia coefficient of each circuit; a filtering module, used to filter a set of high-risk circuits from each output circuit based on the condition that the load inertia coefficient continuously exceeds a predicted threshold within K consecutive sampling periods; and a switching module, used to use the weighted difference between the rated margin rate of each candidate receiving circuit and the load inertia coefficient as a future stability score, and to switch some loads in the high-risk circuit set to the receiving circuit with the highest future stability score; and to correct the predicted threshold and the K value based on the prediction accuracy of historical switching.

[0007] Thirdly, a power adaptive distribution device for a power distribution cabinet with multiple circuits is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the power adaptive distribution device for the power distribution cabinet with multiple circuits to execute the aforementioned power adaptive distribution method for the power distribution cabinet with multiple circuits.

[0008] Fourthly, a computer-readable storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the aforementioned multi-circuit power adaptive allocation method for power distribution cabinets.

[0009] The technical solution provided in this application synchronously collects data at a fixed sampling period on the incoming side of each output circuit of the distribution cabinet, storing the current values ​​of each circuit at continuous moments in a rolling update manner into the circuit current time-series matrix. This enables the control unit to, for the first time, have the ability to completely record the historical evolution trajectory of the load of each circuit, unlike the single-point acquisition method in the prior art that only retains the instantaneous current value. Based on this, second-order difference operations are performed on the time-series data of each row of the circuit current time-series matrix to obtain the load change acceleration of each circuit. The load change acceleration is then divided by the rated margin of each circuit to obtain the load inertia coefficient of each circuit. The load inertia coefficient unifies the accelerating trend of load growth and the remaining safety margin into a single risk quantification index, enabling the system to identify high-risk circuits with strong load growth and narrowing safety margins before the current reaches the overload threshold. This fundamentally changes the power allocation decision from a passive response to an active prediction, solving the response lag problem caused by simply relying on the current threshold trigger in the prior art.

[0010] Furthermore, using the load inertia coefficient consistently exceeding a predicted threshold over several consecutive sampling periods as a screening criterion, a set of high-risk loops is obtained through the accumulation and decrement mechanism of the confirmation counter. This accurately distinguishes short-term shocks such as inductive load initiation from actual continuous load growth in the time dimension, avoiding the risk of erroneous handover caused by directly exposing the sensitivity of differential operations to short-term disturbances to the handover triggering logic. In selecting the handover target, the weighted difference between the rated margin rate and the load inertia coefficient of each candidate receiving loop is used as the future stability score. The load growth inertia of the receiving loop itself is included in the score weight, ensuring that the handover target not only has sufficient current load margin but also a stable load trend. This solves the defect in existing technologies that only use the lightest current load as the receiving target while ignoring the growth trend of the receiving loop itself, leading to cascading overloads. Ultimately, the prediction threshold and confirmation window length were adjusted based on the prediction accuracy of historical switching, enabling the entire power allocation strategy to continuously optimize parameter configuration as the operating scenario changes. In scenarios with strong load regularity, the prediction threshold was narrowed to improve sensitivity, while in scenarios with drastic load fluctuations, the prediction threshold was expanded and the confirmation window was extended to enhance anti-disturbance capability, thus achieving long-term adaptability of the power allocation strategy to different operating scenarios. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 is a schematic diagram of an embodiment of the power adaptive allocation method for multiple circuits in a distribution cabinet according to the present application; Figure 2 is a schematic diagram of an embodiment of the power adaptive allocation system for multiple circuits in a distribution cabinet according to the present application; Figure 3 is a schematic block diagram of the structure of the power adaptive allocation device for multiple circuits in a distribution cabinet according to the present invention. Detailed Implementation

[0013] This application provides a method and system for adaptive power distribution across multiple circuits in a power distribution cabinet. The terms "first," "second," "third," "fourth," etc. (if present)," in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to Figure 1. One embodiment of the power adaptive allocation method for multi-circuit power distribution in this application includes: Step S1: Synchronously collect the real-time current values ​​of each output circuit of the distribution cabinet at a fixed sampling period, and store the current values ​​of each circuit at consecutive M time points in an N-row × M-column circuit current time sequence matrix in a rolling update manner; Specifically, the number of columns of the circuit current time sequence matrix is ​​set to 300, corresponding to a 30-second historical window when the sampling period is 100 milliseconds. The 30-second selection is based on the fact that in industrial power distribution scenarios, the shortest stable period of the periodic fluctuation of the load (such as motor start-stop, frequency conversion speed regulation) is usually not less than 10 seconds. The 30-second window can cover at least two complete load fluctuation cycles, so that the load change acceleration obtained by the second-order difference operation can reflect the real growth trend of the circuit load, rather than the false acceleration caused by instantaneous disturbance. The number of rows is determined by the actual number of output circuits of the distribution cabinet. Each row is stored independently, and each row is synchronously advanced during rolling updates to ensure the time alignment of the historical data of each circuit.

[0015] Step S2: Perform second-order difference operations on the time series data of each row of the loop current time series matrix to obtain the load change acceleration of each loop; divide the load change acceleration by the rated margin of each loop to obtain the load inertia coefficient of each loop; specifically, the construction logic of the load inertia coefficient is: divide by the load change acceleration as the numerator and the rated margin as the denominator. The rated margin is the difference between the upper limit of the rated current of each loop and the current real-time current, reflecting the remaining safe space of the loop from the overload state. The load change acceleration reflects whether the current growth trend of the loop is still accelerating. The physical meaning of the quotient of the two is: within the current remaining safe space, the urgency of the current growth trend of the loop—the smaller the remaining safe space and the greater the growth acceleration, the higher the load inertia coefficient and the more concentrated the overload risk. When the load change acceleration is not greater than zero, it indicates that the loop current is in a decreasing or stable state, the load inertia coefficient is set to zero, and the subsequent screening process is not triggered.

[0016] Step S3: Based on the condition that the load inertia coefficient continuously exceeds the predicted threshold for K consecutive sampling periods, a set of high-risk circuits is selected from each output circuit. Specifically, the confirmation window length is set to five sampling periods, corresponding to 500 milliseconds. In industrial power distribution scenarios, the duration of the inrush current generated when an inductive load starts is usually no more than 200 milliseconds, i.e., no more than two sampling periods, which is insufficient for the confirmation counter to accumulate to five. However, in real scenarios where the load continuously increases, the duration for which the load inertia coefficient exceeds the predicted threshold is far greater than 500 milliseconds, and the confirmation counter will steadily accumulate to five, thereby triggering the selection of the high-risk circuit set. The predicted threshold is set to 0.05, which means that when the load acceleration intensity within a unit rated margin of a circuit exceeds 0.05, a predicted overload risk is determined. The adjustment range of the predicted threshold is limited to between 0.02 and 0.15, and the adjustment range of the confirmation window length is limited to between three and eight sampling periods. Both boundaries are set based on the response speed requirements of the distribution cabinet under extreme light load and extreme heavy load scenarios to prevent parameters from drifting to the range that would cause system failure.

[0017] Step S4: Use the weighted difference between the rated margin rate and the load inertia coefficient of each candidate receiving circuit as the future stability score, and switch some loads in the high-risk circuit set to the receiving circuit with the highest future stability score; based on the prediction accuracy of historical switching, correct the prediction threshold and K value.

[0018] Specifically, in the future stability scoring, the weighting factor for the rated margin rate is set to 0.7, and the weighting factor for the load inertia coefficient compensation is set to 0.3. The rated margin rate has a higher weighting than the inertia coefficient compensation because: the primary condition for the receiving circuit is that it currently has sufficient load capacity; the inertia coefficient compensation, as a secondary condition, is used to further screen the circuit with the most stable load trend among multiple candidate circuits with similar margins. The sum of the two weights is one, ensuring score normalization. In the calculation of the switching current, the difference between the current and 70% of the rated current limit is taken for the high-risk circuit side. The purpose is to reduce the current of the high-risk circuit to below 70% of the rated value, leaving sufficient margin to cope with possible subsequent load fluctuations. For the receiving circuit side, 50% of the rated margin is taken as the upper limit to prevent the receiving circuit from being overloaded in a single switch. The minimum of the two is taken as the final switching current, ensuring that the switching decision is within the safe range for both circuits.

[0019] In one specific embodiment, step S1 includes: configuring current transformers with strain ratios based on the rated current of each output circuit on the incoming side of the distribution cabinet, synchronously collecting the real-time current value of each circuit at a fixed sampling period to obtain the current collection value of each circuit at each moment; storing the current collection value into the corresponding row and column positions of the circuit current time sequence matrix according to the circuit number and sampling time, deleting the earliest column for each newly collected column of data, and maintaining the circuit current time sequence matrix in a rolling update manner so that it always saves the current collection value of each circuit within a continuous fixed time period; performing subtraction operations on each circuit sequentially based on the current collection value of each circuit in the current column of the circuit current time sequence matrix and the pre-stored upper limit of the rated current of each circuit to obtain the rated margin of each circuit; comparing the rated margin with zero value, filtering out the circuits with rated margin not greater than zero to obtain the instant overload circuit mark set, the circuits in the instant overload circuit mark set are directly incorporated into the load switching process, and the circuits with rated margin greater than zero enter the load inertia coefficient calculation process.

[0020] Specifically, the loop current time-series matrix is ​​a two-dimensional data structure with the number of rows equal to the total number of output loops in the distribution cabinet and a fixed number of columns of 300. Elements in a specific row and column of the matrix store the real-time current acquisition value of the corresponding numbered loop at the corresponding sampling time, in amperes. The rolling update is implemented as follows: after every 100-millisecond sampling cycle, the newly acquired current values ​​of each loop within that cycle are added as a new column to the last column of the matrix, while the earliest column is deleted, ensuring the matrix always maintains 300 columns, corresponding to a 30-second historical window. The 30-second window is set based on the fact that the shortest stable period of load periodic fluctuations in industrial power distribution scenarios is usually no less than 10 seconds. 30 seconds can cover at least two complete fluctuation cycles, ensuring that the load change acceleration obtained from subsequent second-order difference calculations reflects the true load growth trend rather than instantaneous disturbances.

[0021] Rated margin is defined as the difference between the upper limit of the rated current of each circuit and the current real-time current acquisition value. The upper limit of the rated current is pre-stored in the control unit by the distribution cabinet's nameplate parameters during system initialization and remains fixed. The physical meaning of rated margin is the remaining current safety space of the circuit from overload conditions, measured in amperes. A rated margin not greater than zero indicates that the current current of the circuit has reached or exceeded the rated upper limit; such circuits constitute an instant overload circuit marker set and are directly incorporated into the load switching process. Circuits with a rated margin greater than zero are still within the safe operating range and enter the load inertia coefficient calculation process. Both branch paths use whether the rated margin is greater than zero as the sole criterion, covering all possible values ​​of the rated margin, and there are no undefined states.

[0022] In one specific embodiment, step S2 includes: performing first-order difference operations on the time-series data of each row in the loop current time-series matrix to obtain the current change between adjacent sampling times of each loop; performing mean smoothing on the current change based on a sliding window with a length of five sampling points to obtain the load change rate of each loop; performing first-order difference operations on the load change rate to obtain the rate change between adjacent times of each loop; performing mean smoothing on the rate change based on a sliding window with a length of three sampling points to obtain the load change acceleration of each loop; dividing the load change acceleration by the rated margin of the corresponding loop to obtain the load inertia coefficient of each loop; and setting the load inertia coefficient of the corresponding loop to zero when the load change acceleration is not greater than zero.

[0023] Specifically, the difference between two adjacent columns in a row of the loop current time-series matrix is ​​taken, i.e., the current sampling value at a later time step minus the current sampling value at the previous time step, to obtain the current change of the loop between adjacent time steps, in amperes per sampling period. The resulting current change sequence is averaged using a sliding window of five sampling points, i.e., the arithmetic mean of the current changes at five consecutive time steps, to obtain the load change rate at the current time step. The sliding window length is set to 500 milliseconds corresponding to five sampling points, based on the principle that the interference amplitude of single sampling noise on the difference result usually does not exceed two sampling periods, and the five-point mean is sufficient to eliminate noise interference without excessively smoothing the true load change trend. Based on the obtained load change rate sequence, a first-order difference operation is performed again, i.e., the load change rate at a later time step is subtracted from the load change rate at the previous time step, to obtain the rate change between adjacent time steps for each loop. Then, the rate change is averaged using a sliding window of three sampling points to obtain the load change acceleration for each loop. The second sliding window length is three sampling points instead of five because the acceleration sequence has already undergone two differential processing steps, and the data fluctuation amplitude is smaller than that of the rate sequence. The three-point average is sufficient to eliminate residual noise. If the five-point average is used, it will cause the acceleration response to lag, weakening the timeliness of the prediction.

[0024] The load inertia coefficient, calculated by dividing the load change acceleration by the rated margin of the corresponding circuit, physically represents the urgency of the current growth trend within the current safe space. A smaller rated margin indicates the circuit is closer to overload; a larger load change acceleration indicates a stronger current growth momentum; and a larger quotient indicates a more concentrated risk of overload. When the load change acceleration is not greater than zero, it indicates that the current growth trend has stabilized or turned downward, and there is no anticipated overload risk. The load inertia coefficient is set to zero, and the subsequent screening process for high-risk circuits is not triggered. The zeroing condition for the load inertia coefficient, together with the entry condition of a rated margin greater than zero, constitutes complete state coverage, ensuring that each circuit has a clear processing path in each sampling period.

[0025] In one specific embodiment, step S3 includes: comparing the load inertia coefficient of each loop with a predicted threshold; for loops whose load inertia coefficient continuously exceeds the predicted threshold, incrementing the confirmation counter of the corresponding loop by one unit; for loops whose load inertia coefficient is lower than the predicted threshold, decrementing the confirmation counter of the corresponding loop by one unit, and ensuring that the value of the decremented confirmation counter is not lower than zero; comparing the cumulative value of the confirmation counter of each loop with the confirmation window length, and filtering out high-risk loop sets from loops whose cumulative confirmation counter value reaches the confirmation window length; comparing the load inertia coefficient of the loops included in the high-risk loop set with half of the predicted threshold, and removing loops whose load inertia coefficient is lower than half of the predicted threshold for three consecutive sampling periods from the high-risk loop set, and resetting the confirmation counter of the loop to zero.

[0026] Specifically, the confirmation counter is an independently maintained integer count variable for each circuit, initially set to zero, with its value limited to between zero and the confirmation window length. Within each sampling period, if the load inertia coefficient of a circuit exceeds the predicted threshold, the confirmation counter for that circuit is incremented by one unit; if it falls below the predicted threshold, it is decremented by one unit, ensuring the value does not fall below zero. The confirmation window length is set to five sampling periods, corresponding to 500 milliseconds. This value is based on the following: In industrial power distribution scenarios, the duration of the inrush current generated when an inductive load starts typically does not exceed 200 milliseconds, i.e., no more than two sampling periods. The abnormal increase in the load inertia coefficient caused by the inrush current cannot cause the confirmation counter to accumulate to five through alternating increments and decrements. However, in real, continuous load growth scenarios, the load inertia coefficient will stably exceed the predicted threshold over multiple consecutive sampling periods. After the confirmation counter stably accumulates to five, screening is triggered, thus accurately distinguishing short-term impact disturbances from real load growth in the time dimension. This is an anti-disturbance capability that existing single-threshold comparison triggering mechanisms lack.

[0027] If a loop already included in the high-risk loop set has a load inertia coefficient that is below half of the predicted threshold for three consecutive sampling periods, it will be removed from the high-risk loop set and its confirmation counter will be reset to zero. The removal criterion uses half of the predicted threshold rather than the threshold itself because: when the load inertia coefficient fluctuates slightly around the predicted threshold, using the threshold itself as the removal criterion would cause the loop to repeatedly enter and exit the high-risk set, leading to frequent triggering and cancellation of handover commands. Using half as the removal criterion requires the load inertia coefficient to clearly fall below the predicted threshold by a sufficiently large margin before it can be confirmed that the overload risk of the loop has been substantially eliminated. The requirement of three consecutive sampling periods corresponds to 300 milliseconds, further eliminating the possibility of the load inertia coefficient rising again after a brief drop. This, combined with the five-period confirmation in the accumulation phase, forms an asymmetric design—strict entry conditions and even stricter exit conditions—preventing instability in handover decisions due to frequent changes in the high-risk loop set.

[0028] In one specific embodiment, step S4, using the weighted difference between the rated margin rate and the load inertia coefficient of each candidate receiving circuit as the future stability score, includes: excluding circuits from the high-risk circuit set and the instantaneous overload circuit marker set from each output circuit, and forming a candidate receiving circuit set from the remaining circuits; obtaining the rated margin rate of each candidate receiving circuit based on the ratio of the rated margin to the upper limit of the rated current of each candidate receiving circuit in the candidate receiving circuit set; assigning the rated margin rate to a first weighting coefficient, and assigning the complement of the ratio of the load inertia coefficient of each candidate receiving circuit to the maximum load inertia coefficient of all circuits to a second weighting coefficient, summing the two weighted results to obtain the future stability score of each candidate receiving circuit; and determining the circuit with the highest future stability score in the candidate receiving circuit set as the target receiving circuit.

[0029] Specifically, circuits from both the high-risk circuit set and the instant overload circuit marker set are simultaneously excluded from all output circuits of the distribution cabinet. The remaining circuits are then included in the candidate receiving circuit set. The criteria for simultaneous exclusion of both types of circuits are as follows: circuits in the high-risk circuit set have a load inertia coefficient exceeding the pre-judgment threshold, indicating a pre-judged overload risk and thus lacking the capacity to accept transferred loads; circuits in the instant overload circuit marker set have a current rated margin no greater than zero, indicating an overload state and similarly lacking the capacity to accept loads. The rated margin rate is defined as the ratio of the rated margin of each candidate receiving circuit to its rated current upper limit, reflecting the proportion of the circuit's current remaining safety space to its rated capacity. The value ranges from zero to one; a higher value indicates a more ample current carrying capacity for the circuit. The complement of the ratio of the load inertia coefficient to the maximum load inertia coefficient in all loops is calculated as follows: divide the load inertia coefficient of a candidate receiving loop by the maximum load inertia coefficient in all loops to obtain the normalized inertia coefficient, and then subtract the normalized inertia coefficient from one to obtain the complement. The complement value is also between zero and one. The larger the complement value, the more stable the load growth trend of the loop itself.

[0030] The first weighting coefficient is set to 0.7, and the second weighting coefficient is set to 0.3. Their sum is 1, ensuring the normalization of the future stability score. The reason for setting the first weighting coefficient higher than the second weighting coefficient is as follows: the primary condition for the receiving circuit is that it currently has sufficient physical carrying capacity, and the rated margin rate directly reflects this condition, thus assigning it a higher weight. The load inertia coefficient is used as a secondary condition to further screen among multiple candidate circuits with similar rated margin rates to identify the circuit with the most stable load trend, preventing the load from being transferred to a circuit that, although currently having sufficient margin, is experiencing rapid load growth, thereby triggering a chain reaction of overload. The future stability score is obtained by summing the two weighted results. The candidate receiving circuit with the highest score is selected as the target receiving circuit. The target receiving circuit is uniquely determined, and there is no ambiguity when there is a tie for the highest score. If there are identical scores, the circuit with the smaller circuit number is given priority.

[0031] In one specific embodiment, step S4, switching a portion of the load in the high-risk circuit set to the receiving circuit with the highest future stability score, includes: taking the minimum value between the difference between the current acquisition value of each circuit in the high-risk circuit set and 70% of the rated current upper limit, and 50% of the rated margin of the target receiving circuit, to obtain the switching current; multiplying the switching current by the rated voltage of the corresponding circuit to obtain the switching power; and issuing a switching command to the intelligent switching module based on the switching power to transfer a portion of the load of the corresponding circuit in the high-risk circuit set to the target receiving circuit.

[0032] Specifically, the calculation of the switching current involves two constraints: The first constraint comes from the high-risk circuit side, where the switching limit is the difference between the current current acquisition value of the corresponding circuit in the high-risk circuit set and 70% of its rated current limit. This difference physically represents the amount of current transferred to reduce the current of the high-risk circuit to 70% of its rated current limit. The 70% rated current limit is set as the target voltage drop level to ensure that the high-risk circuit current is reduced to below 70% of its rated value, providing sufficient safety margin after switching to cope with subsequent load fluctuations without triggering a high-risk determination. The second constraint comes from the target receiving circuit side, where the switching limit is 50% of the target receiving circuit's current rated margin. This value is set based on the principle that a single switch only occupies half of the remaining load capacity of the target receiving circuit, reserving the other half as a buffer for load fluctuations within the target receiving circuit itself, preventing the target receiving circuit from falling into a high-risk state due to excessive load in a single operation. The final switching current is obtained by taking the minimum value of the two constraints. The logic for taking the minimum value is to simultaneously satisfy the voltage drop requirement of the high-risk circuit side and the load limit of the target receiving circuit side. The more stringent one of the two constraints is selected as the switching amount to ensure that the switching decision is within the safe range for both circuits.

[0033] The switching power is calculated by multiplying the switching current by the rated voltage of the corresponding circuit. The rated voltage is the nominal voltage value of the corresponding circuit in the distribution cabinet, pre-stored in the control unit during system initialization, and is measured in volts. The switching power is measured in watts. The intelligent switching module consists of a solid-state relay or a smart circuit breaker. The control unit sends a switching command to the intelligent switching module based on the switching power. The intelligent switching module then disconnects the load with a rated power equal to the switching power in the corresponding circuit of the high-risk circuit set from the original circuit and connects it to the target receiving circuit, completing the physical transfer of part of the load. The switching command includes three parameters: the high-risk circuit number, the target receiving circuit number, and the switching power. These three parameters together determine a complete switching operation, eliminating any ambiguity caused by missing parameters.

[0034] In one specific embodiment, step S4, based on the prediction accuracy of historical switching, modifies the prediction threshold and confirmation window length, including: after the switching command is executed, using a fixed evaluation time as a window, collecting evolution data of the current acquisition values ​​of the corresponding circuits in the original high-risk circuit set; judging whether the trend extrapolation result corresponding to the load inertia coefficient before switching is consistent with the actual current evolution direction based on the evolution data, and obtaining the prediction accuracy mark for each switching; based on the historical switching records of a fixed number of consecutive switching records, the prediction accuracy mark is accurate, and the current acquisition value of the corresponding circuit in the original high-risk circuit set drops to below 75% of the rated current upper limit after switching. The historical handover prediction accuracy rate is obtained by calculating the percentage of handovers where the current acquisition value of the target receiving circuit does not exceed 85% of the rated current limit. The historical handover prediction accuracy rate is compared with a first proportional threshold. If the historical handover prediction accuracy rate is higher than the first proportional threshold, the prediction threshold is lowered by a fixed proportion. The historical handover prediction accuracy rate is compared with a second proportional threshold. If the historical handover prediction accuracy rate is lower than the second proportional threshold, the prediction threshold is raised by a fixed proportion, and the confirmation window length is increased by one unit. The adjustment range of the prediction threshold is limited to a first preset range, and the adjustment range of the confirmation window length is limited to a second preset range.

[0035] Specifically, the fixed evaluation duration is set to 10 seconds, corresponding to 100 sampling periods. The 10-second setting is based on the fact that after the switching command is executed, the current response of the high-risk circuit needs several sampling periods to stably reflect the switching effect. In industrial power distribution scenarios, the current stabilization time after load transfer is usually no more than 5 seconds, and a 10-second window is sufficient to cover the complete current response process. The trend extrapolation judgment logic is as follows: take the average load change rate of the high-risk circuit in the last 5 sampling periods before the switching, multiply this average value by the number of sampling periods corresponding to the evaluation duration to obtain the predicted increment of the circuit current under the assumption of no switching. Compare the sum of the current collected value and the predicted increment with the rated current upper limit. If the predicted result exceeds the rated current upper limit, the trend extrapolation result is determined to be an overload trend. If the actual current evolution direction of the circuit within the evaluation window is consistent with the trend extrapolation result direction, the prediction accuracy of this switching is marked as accurate; otherwise, it is marked as inaccurate. The number of consecutive fixed times is set to 20. The historical handover prediction accuracy is obtained by dividing the number of handover records in the most recent 20 handover records that simultaneously meet the following conditions: the prediction accuracy is marked as accurate, the current of the original high-risk circuit drops to below 75% of the rated current limit after the handover, and the current of the target receiving circuit does not exceed 85% of the rated current limit by 20.

[0036] The first proportional threshold is set to 0.85, and the second proportional threshold is set to 0.70. The rationale for these settings is as follows: a historical handover prediction accuracy rate higher than 0.85 indicates that the current prediction threshold has sufficient ability to identify load growth trends; therefore, the prediction threshold is lowered by a fixed percentage of 5% to make the system more sensitive to load growth trends. Conversely, a historical handover prediction accuracy rate lower than 0.70 indicates that the current prediction threshold has a misjudgment rate exceeding 30%; therefore, the prediction threshold is increased by a fixed percentage of 10%, and the confirmation window length is increased by one unit to enhance anti-disturbance capabilities. The adjustment range of the prediction threshold is limited to between 0.02 and 0.15. The lower limit of 0.02 corresponds to the minimum identifiable risk intensity of the system under extremely low load fluctuation scenarios; values ​​below this value will lead to a large number of misjudgments. The upper limit of 0.15 corresponds to the maximum tolerable misjudgment intensity of the system under extremely high load fluctuation scenarios; values ​​exceeding this value will cause the system to respond sluggishly to real overload risks. The adjustment range for the confirmation window length is limited to 3 to 8 sampling periods. The lower limit of 3 sampling periods corresponds to 300 milliseconds, which is the shortest confirmation time required to distinguish between inrush current and actual load growth. The upper limit of 8 sampling periods corresponds to 800 milliseconds. Exceeding this value will cause the system to respond to rapid load growth with severe lag.

[0037] The above describes the adaptive power allocation method for multi-circuit power distribution in the embodiments of this application. The following describes the adaptive power allocation system for multi-circuit power distribution in the embodiments of this application. Referring to Figure 2, one embodiment of the adaptive power allocation system for multi-circuit power distribution in the embodiments of this application includes: an extraction module, used to synchronously collect the real-time current values ​​of each output circuit of the distribution cabinet at a fixed sampling period, and store the current values ​​of each circuit at consecutive M time points in an N-row × M-column circuit current time-series matrix in a rolling update manner; and a calculation module, used to perform second-order difference operations on the time-series data of each row of the circuit current time-series matrix to obtain the current values ​​of each circuit. Load change acceleration; the load change acceleration is divided by the rated margin of each circuit to obtain the load inertia coefficient of each circuit; a screening module is used to screen out a set of high-risk circuits from each output circuit based on the condition that the load inertia coefficient continuously exceeds the predicted threshold for K consecutive sampling periods; a switching module is used to switch some loads in the set of high-risk circuits to the receiving circuit with the highest future stability score based on the weighted difference between the rated margin rate of each candidate receiving circuit and the load inertia coefficient; the predicted threshold and the K value are corrected based on the prediction accuracy of historical switching.

[0038] Figure 2 above describes the multi-circuit power adaptive distribution system of the distribution cabinet in this embodiment of the invention from the perspective of modular functional entities. The following describes the multi-circuit power adaptive distribution device of the distribution cabinet in this embodiment of the invention from the perspective of hardware processing.

[0039] Referring to Figure 3, this embodiment of the invention also provides a multi-circuit power adaptive allocation device for a power distribution cabinet. This device can be a server, and its internal structure is as shown in Figure 3. The device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0040] Those skilled in the art will understand that the structure shown in Figure 3 is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the multi-circuit power adaptive distribution device of the power distribution cabinet to which the present invention is applied.

[0041] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the power distribution cabinet multi-circuit adaptive power allocation method.

[0042] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0043] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a multi-circuit power adaptive distribution device in a power distribution cabinet (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0044] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for adaptive power allocation across multiple circuits in a distribution cabinet, characterized in that, The method includes: Step S1: Synchronously collecting the real-time current values ​​of each output circuit of the distribution cabinet at a fixed sampling period, and storing the current values ​​of each circuit at M consecutive moments in a rolling update manner into an N-row × M-column circuit current time series matrix; Step S2: Performing second-order difference operations on the time series data of each row of the circuit current time series matrix to obtain the load change acceleration of each circuit; dividing the load change acceleration by the rated margin of each circuit to obtain the load inertia coefficient of each circuit; Step S3: Selecting a set of high-risk circuits from each output circuit based on the condition that the load inertia coefficient continuously exceeds the predicted threshold for K consecutive sampling periods; Step S4: Using the weighted difference between the rated margin rate of each candidate receiving circuit and the load inertia coefficient as the future stability score, switching some loads in the set of high-risk circuits to the receiving circuit with the highest future stability score; and correcting the predicted threshold and the K value based on the prediction accuracy of historical switching.

2. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 1, characterized in that, Step S1 includes: on the incoming side of each output circuit of the distribution cabinet, configuring current transformers with strain ratios based on the rated current of each circuit, synchronously collecting the real-time current value of each circuit at a fixed sampling period to obtain the current collection value of each circuit at each time; storing the current collection value into the corresponding row and column positions of the circuit current time sequence matrix according to the circuit number and sampling time, deleting the earliest column for each newly collected column of data, and maintaining the circuit current time sequence matrix in a rolling update manner to ensure that it always saves the current collection value of each circuit within a continuous fixed time period; based on the current collection value of each circuit in the current column of the circuit current time sequence matrix and the pre-stored upper limit of the rated current of each circuit, performing a subtraction operation on each circuit in turn to obtain the rated margin of each circuit; comparing the rated margin with zero value, filtering out the circuits with rated margin not greater than zero to obtain an instant overload circuit mark set, the circuits in the instant overload circuit mark set are directly incorporated into the load switching process, and the circuits with rated margin greater than zero enter the load inertia coefficient calculation process.

3. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 2, characterized in that, Step S2 includes: performing first-order difference operations on the time-series data of each row in the loop current time-series matrix to obtain the current change between adjacent sampling times of each loop; performing mean smoothing on the current change based on a sliding window with a length of five sampling points to obtain the load change rate of each loop; performing first-order difference operations on the load change rate to obtain the rate change between adjacent times of each loop; performing mean smoothing on the rate change based on a sliding window with a length of three sampling points to obtain the load change acceleration of each loop; dividing the load change acceleration by the rated margin of the corresponding loop to obtain the load inertia coefficient of each loop; and setting the load inertia coefficient of the corresponding loop to zero when the load change acceleration is not greater than zero.

4. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 3, characterized in that, Step S3 includes: comparing the load inertia coefficient of each loop with a predicted threshold; for loops whose load inertia coefficient continuously exceeds the predicted threshold, incrementing the confirmation counter of the corresponding loop by one unit; for loops whose load inertia coefficient is lower than the predicted threshold, decrementing the confirmation counter of the corresponding loop by one unit, and ensuring that the value of the decremented confirmation counter is not lower than zero; comparing the cumulative value of the confirmation counter of each loop with the confirmation window length, and filtering out high-risk loop sets from loops whose cumulative confirmation counter value reaches the confirmation window length; comparing the load inertia coefficient of the loops already included in the high-risk loop set with half of the predicted threshold, and removing loops whose load inertia coefficient is lower than half of the predicted threshold for three consecutive sampling periods from the high-risk loop set, and resetting the confirmation counter of the loop to zero.

5. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 4, characterized in that, In step S4, the future stability score is calculated using the weighted difference between the rated margin rate and the load inertia coefficient of each candidate receiving circuit. This includes: excluding circuits from the high-risk circuit set and the instantaneous overload circuit marker set from each output circuit, and forming a candidate receiving circuit set from the remaining circuits; obtaining the rated margin rate of each candidate receiving circuit based on the ratio of the rated margin to the upper limit of the rated current for each candidate receiving circuit in the candidate receiving circuit set; assigning a first weighting coefficient to the rated margin rate, and assigning a second weighting coefficient to the complement of the ratio of the load inertia coefficient of each candidate receiving circuit to the maximum value of the load inertia coefficient in all circuits; summing the two weighted results to obtain the future stability score of each candidate receiving circuit; and determining the circuit with the highest future stability score in the candidate receiving circuit set as the target receiving circuit.

6. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 5, characterized in that, In step S4, switching a portion of the load in the high-risk circuit set to the receiving circuit with the highest future stability score includes: taking the minimum value between the current acquisition value of each circuit in the high-risk circuit set and 70% of the rated current upper limit, and 50% of the rated margin of the target receiving circuit, to obtain the switching current; multiplying the switching current by the rated voltage of the corresponding circuit to obtain the switching power; and issuing a switching command to the intelligent switching module based on the switching power to transfer a portion of the load of the corresponding circuit in the high-risk circuit set to the target receiving circuit.

7. The multi-circuit power adaptive allocation method for power distribution cabinets according to claim 6, characterized in that, In step S4, the prediction threshold and the confirmation window length are corrected based on the historical switching prediction accuracy. This includes: after the switching command is executed, using a fixed evaluation time as a window, collecting evolution data of the current acquisition value of the corresponding circuit in the original high-risk circuit set; judging whether the trend extrapolation result corresponding to the load inertia coefficient before the switching is consistent with the actual current evolution direction based on the evolution data, and obtaining the prediction accuracy mark for each switching; based on the historical switching records of a fixed number of consecutive switching records, the prediction accuracy mark is accurate, and the current acquisition value of the corresponding circuit in the original high-risk circuit set drops to below 75% of the rated current upper limit after the switching, and the target connection... The historical switching prediction accuracy rate is obtained by calculating the percentage of switching times where the current acquisition value of the recovery path does not exceed 85% of the rated current upper limit. This historical switching prediction accuracy rate is then compared with a first proportional threshold. If the historical switching prediction accuracy rate is higher than the first proportional threshold, the prediction threshold is lowered by a fixed proportion. Conversely, the historical switching prediction accuracy rate is compared with a second proportional threshold. If the historical switching prediction accuracy rate is lower than the second proportional threshold, the prediction threshold is raised by a fixed proportion, and the confirmation window length is increased by one unit. The adjustment range of the prediction threshold is limited to a first preset interval, and the adjustment range of the confirmation window length is limited to a second preset interval.

8. A multi-circuit adaptive power distribution system for a power distribution cabinet, characterized in that, To implement the power adaptive allocation method for multiple circuits in a distribution cabinet as described in any one of claims 1-7, the power adaptive allocation system for multiple circuits in a distribution cabinet comprises: an extraction module, used to synchronously collect the real-time current values ​​of each output circuit of the distribution cabinet at a fixed sampling period, and store the current values ​​of each circuit at consecutive M time points in a rolling update manner into an N-row × M-column circuit current time series matrix; a calculation module, used to perform second-order difference operations on the time series data of each row of the circuit current time series matrix to obtain the load change acceleration of each circuit; and to divide the load change acceleration by the rated margin of each circuit to obtain the load inertia coefficient of each circuit; a screening module, used to screen out a set of high-risk circuits from each output circuit based on the condition that the load inertia coefficient continuously exceeds a predicted threshold within K consecutive sampling periods; and a switching module, used to switch some loads in the set of high-risk circuits to the receiving circuit with the highest future stability score based on the weighted difference between the rated margin rate of each candidate receiving circuit and the load inertia coefficient; and to correct the predicted threshold and the K value based on the predicted accuracy rate of historical switching.

9. A multi-circuit power adaptive distribution device for a power distribution cabinet, characterized in that, It includes a memory and a processor, the memory storing a computer program that can run on the processor, and the processor executing the computer program to implement the multi-circuit power adaptive allocation method for the distribution cabinet as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it causes the processor to execute the power adaptive allocation method for multiple circuits in the distribution cabinet as described in any one of claims 1 to 7.

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