Transformer capacity constraint-oriented charging pile dynamic power scheduling method and system

Abstract

The invention relates to the technical field of charging pile power dispatching, and discloses a transformer capacity constraint-oriented charging pile dynamic power dispatching method and system, and the transformer capacity constraint-oriented charging pile dynamic power dispatching system comprises a data collection module, a distributable power budget calculation module, a strategy distribution module and an instruction issuing module. The transformer capacity constraint-oriented charging pile dynamic power scheduling method comprises the following steps of: acquiring states of a transformer and a charging pile in real time, and identifying communication abnormal equipment; deducting an uncontrolled load and a communication abnormal pile conservative limit based on a transformer logic total capacity under a safety threshold, and calculating a group distributable power budget; single pile target power is calculated through multi-strategy combination under budget constraint; and performing slope limit smoothing processing on the target power and then issuing an execution instruction. According to the invention, through an abnormal equipment conservative deduction mechanism and an instruction time domain smoothing technology, safe operation of the transformer is ensured under a communication fault, and the impact of power abrupt change on hardware is eliminated.

Description

Technical Field

[0001] This invention relates to the field of charging pile power scheduling technology, specifically to a dynamic power scheduling method and system for charging piles oriented towards transformer capacity constraints. Background Technology

[0002] With the increasing number of new energy vehicles, transformer capacity has become a key bottleneck limiting the number of vehicles that charging stations can serve simultaneously. Existing power dispatching technologies rely on real-time communication data to maintain closed-loop control, calculating the total load by collecting real-time voltage and current data from charging piles. However, the on-site network environment is complex, and the communication connection between charging piles and controllers lacks absolute stability. In the event of communication data packet loss or heartbeat interruption, the central control unit cannot obtain the real-time power of the disconnected equipment. Existing technologies typically process the power of disconnected equipment as zero or maintain the value from the previous moment, ignoring the fact that disconnected equipment is often operating at full load. Once there is a deviation between the actual power and the estimated power of the disconnected equipment, the total load of the transformer can easily exceed the physical safety boundary, causing the upstream circuit breaker to trip and resulting in a power outage at the entire station.

[0003] Furthermore, existing power allocation algorithms are mostly based on static optimization solutions using discrete time steps. When vehicle demand changes significantly, the calculation results of adjacent scheduling cycles exhibit abrupt changes. Directly sending such power commands with large jumps to the underlying execution mechanism causes drastic fluctuations in the charging module's output current. Current surges accelerate the aging of power devices, affecting equipment lifespan, introducing power quality risks, and even triggering the overcurrent protection mechanism of the vehicle's battery management system, leading to unexpected charging interruptions.

[0004] Meanwhile, traditional power allocation strategies often employ a single, average allocation and a first-come, first-served logic. Faced with differences in battery charge states among different vehicles and the urgent charging needs of operational vehicles, this single allocation model lacks flexibility. When power resources are scarce, it cannot differentiate scheduling based on the actual urgency and user level, resulting in excessively long waiting times for vehicles with low battery levels and limited power resource utilization efficiency. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a dynamic power scheduling method and system for charging piles oriented towards transformer capacity constraints. It solves the problem that existing technologies struggle to accurately calculate the total transformer load under conditions of communication anomalies in some charging piles, leading to capacity over-limit tripping. It also solves the problem that discrete scheduling commands generate power surges that cause current impacts on charging equipment hardware and the power grid, and addresses the problem that the lack of flexibility in a single power allocation mode limits the efficiency of power resource utilization.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] The first aspect of this invention provides a dynamic power scheduling method for charging piles oriented towards transformer capacity constraints, the method comprising the following steps:

[0008] The system performs data acquisition and status management by acquiring the physical operating parameters of the transformer and the operating status data of each charging pile within the transformer power supply group through periodic polling and / or event triggering mechanisms. The operating status data includes the communication connection status of the charging pile, fault alarm signals, and vehicle battery management system request data. Based on the acquired data, the system obtains the power values ​​of uncontrolled loads within the transformer power supply group and performs non-negative or upper limit constraint corrections on the power of the uncontrolled loads. Simultaneously, the system monitors the communication connection status of the charging piles in real time and identifies abnormal charging piles with communication interruptions or data loss based on continuous heartbeat loss or data packet loss rate threshold judgment logic.

[0009] A robust deduction-based calculation of the allocable power budget for the transformer power supply group is performed. This step aims to determine the net power available for allocation to controlled charging piles at the current moment. The calculation process is based on the baseline safety threshold power determined by the total physical capacity of the transformer and the safety threshold coefficient. First, the power of uncontrolled loads after constraint correction is deducted, and then the conservative allowance power of all charging piles marked as having communication abnormalities is deducted. The setting strategy for the conservative allowance power is diverse, covering at least one of the equipment nameplate rated power, historical operating peak power, upper bound of historical statistical quantiles, or upper bound of the most recent N-period estimate. The allocable power budget for the transformer power supply group is calculated through the above deduction operation, and a non-negative logic correction is performed on the result.

[0010] The system implements a multi-strategy power allocation. Under the hard constraint of the allocable power budget of the transformer power supply group, it calculates the target power of each normal charging pile participating in the regulation within the transformer power supply group. This step is configured with multiple switchable allocation strategy logics, especially the battery state response strategy. In addition to supporting the determination of high and low charge thresholds, it also supports allocating intermediate weights or determining weights according to mapping functions when the battery state of charge is between two thresholds. The system ensures through global constraint logic that the sum of the target power of all charging piles participating in the regulation is strictly less than or equal to the allocable power budget. After the initial calculation of the target power, a low-power truncation process is performed based on the minimum physical operating power of the charging pile hardware, and the truncated power quota is recovered into the allocable power budget. The charging piles that have not been truncated are iteratively redistributed.

[0011] The system smoothly adjusts and outputs the execution power command, converting the calculated discrete target power into the final issued execution power command. The system reads the historical command values ​​actually issued in the previous scheduling cycle, calculates the maximum allowable change step size in combination with the scheduling cycle and ramp rate limit, and constructs a safe power allowable range. When the change exceeds the preset maximum safe step size, the system activates the slope limit logic to correct the target power within the allowable ramp rate range, generating an execution power command that meets the smoothness constraint. Finally, the execution power command is sent to the underlying controller of each charging pile.

[0012] Furthermore, the method includes a command issuance closed-loop feedback step; after the command is issued, the power tracking deviation is calculated, and when the deviation continues to exceed the threshold, it is determined that the charging pile is in a command out-of-synchronization state, and it is marked as a communication abnormal charging pile and removed from the control set, and then the conservative quota deduction is performed.

[0013] Furthermore, the method employs a dual-mode driving mechanism for triggering; it generates periodic clock signals through a system timer to maintain steady-state scheduling; simultaneously, it scans topology change events in real time (including charging pile online / offline, fault alarms, capacity threshold changes, etc.) to forcibly generate asynchronous event trigger signals; and when the system receives any trigger signal, it freezes all data to generate an input state vector.

[0014] The second aspect of the present invention provides a dynamic power scheduling system for charging piles oriented towards transformer capacity constraints. The system includes a transformer power supply group parameter database, a data acquisition and status management module, a transformer power supply group power aggregation and threshold judgment module, a power budget calculation module, a strategy engine and allocation module, and a smooth adjustment and command issuance module.

[0015] The transformer power supply group parameter database is used to store transformer power supply group level constraint parameters and charging pile basic information; the transformer power supply group level constraint parameters include transformer capacity parameters, safety threshold coefficients and uncontrolled load deduction parameters; the charging pile basic information includes equipment rated power, priority parameters and abnormal charging pile quota power parameters.

[0016] The data acquisition and status management module is configured to acquire real-time operating data of transformers and charging piles, and maintain an online status list of equipment within the transformer power supply group; this module is used to obtain the real-time power of uncontrolled loads and monitor the communication connection status of charging piles, marking devices with communication timeouts or data packet loss as abnormal charging piles; this module is also responsible for generating dual-mode trigger signals based on periodic clocks and asynchronous topology events, and freezing the input status vector.

[0017] The power budget calculation module is configured to execute the accounting logic for the power budget that can be allocated to the group. The module obtains the total physical capacity of the transformer and the safety threshold coefficient, and executes the deduction rule. The deduction rule is defined as subtracting the real-time occupied power of uncontrolled loads from the transformer's safe capacity, and further subtracting the conservative allowance power of charging piles with communication abnormalities. The module outputs the power budget that can be allocated to the transformer power supply group as the boundary condition for subsequent allocation, thereby preventing uncontrollable capacity from being mistakenly included in the power budget.

[0018] The strategy engine and allocation module are configured to receive the allocable power budget of the transformer power supply group and calculate the target power of each charging pile in combination with the vehicle's required power and strategy configuration parameters. The module has a built-in multi-strategy algorithm library that supports the allocation of power resources based on weighting coefficients, priority sorting, or battery state of charge. The module ensures that the sum of the output target power of a single charging pile meets the remaining available capacity limit of the transformer and executes low-power cutoff and power recovery and redistribution logic.

[0019] The smoothing adjustment and command issuance module is configured to perform time-domain smoothing on the target power output by the strategy engine. This module stores the power ramp rate limit value, constructs a safe power allowable range based on the previous cycle command, limits the slope of power mutation, generates a smoothed execution power command and issues it to the charging pile. This module is also responsible for monitoring power tracking deviation, identifying command out-of-step status and executing closed-loop feedback logic.

[0020] This invention constructs a closed-loop control system encompassing physical boundary awareness, abnormal capacity reduction, strategy optimization allocation, and smooth command output through the aforementioned technical solutions. Its core innovation lies in proposing a multi-dimensional conservative reduction mechanism for devices with communication anomalies. Even when some devices lose connection or commands become out of sync, it can still ensure that the transformer is not overloaded by shrinking the allocable power budget. Simultaneously, by combining command smoothing technology and a dual-mode triggering mechanism, it solves the power surge problem caused by discrete scheduling commands and the problem of delayed response to sudden events, achieving a comprehensive improvement in the safety, robustness, and stability of power scheduling at charging stations.

[0021] This invention provides a method and system for dynamic power scheduling of charging piles under transformer capacity constraints. It has the following beneficial effects:

[0022] 1. This invention introduces multi-dimensional anomaly deduction logic when calculating the allocable power budget of the calculation group. It pre-deducts the conservative power allowance corresponding to the charging pile with communication failure from the total physical capacity of the transformer. This conservative allowance can be flexibly selected from the nameplate power, historical peak value or statistical upper limit, avoiding the limitation of a single fixed value. At the same time, combined with the closed-loop feedback mechanism of command issuance, the equipment in the command out-of-synchronization state is included in the anomaly handling process and then performs conservative deduction. This ensures that the system maintains the total load of the transformer within the safe threshold under the condition of communication loss or control failure, and enhances the fault tolerance capability of the scheduling system to deal with various software and hardware failures.

[0023] 2. This invention performs time-domain shaping on the target power sequence output by the strategy engine through a smoothing adjustment and command issuance module, constructs a safe power allowable range based on the previous cycle command and ramp rate limit, limits the power change slope between adjacent scheduling cycles, eliminates the current impact caused by large power step changes on the charging pile hardware circuit and vehicle battery management system, and maintains the stability of DC bus voltage.

[0024] 3. This invention constructs a multi-strategy compatible engine that, while adhering to the group-allocable power budget, supports power allocation calculation based on vehicle demand ratio, user priority ranking, and differentiated weights of battery state of charge. In particular, it supports intermediate weight mapping for scenarios where the SOC is between high and low thresholds, avoiding adjustment gaps. At the same time, it introduces a power recovery and redistribution mechanism after low power truncation, which redistributes scattered power to unmet charging piles, maximizing the utilization of the remaining capacity of the transformer and improving the operational efficiency of charging stations. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the dynamic power scheduling system for charging piles oriented towards transformer capacity constraints according to the present invention.

[0026] Figure 2 This is a schematic diagram of the multi-strategy power allocation strategy engine architecture of the present invention;

[0027] Figure 3 This is a flowchart of the dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to the present invention.

[0028] Figure 4 This is a schematic diagram of the hardware structure of the electronic device of the present invention.

[0029] The system comprises: 11. Group parameter database; 12. Data acquisition and status management module; 13. Group power aggregation and threshold judgment module; 14. Power budget calculation module; 15. Strategy engine and allocation module; 16. Smooth adjustment and command issuance module; 17. Alarm and notification module; 18. Log and analysis module; 19. Configuration interface module; 100. Electronic equipment; 101. Processor; 102. Memory; 103. Communication interface; 104. Bus. Detailed Implementation

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] See attached document Figure 1 , Figure 1 This is a schematic diagram of a dynamic power scheduling system for charging piles under transformer capacity constraints, according to an embodiment of the present invention. The present invention provides a dynamic power scheduling system for charging piles under transformer capacity constraints. The system includes a transformer power supply group parameter database 11, a data acquisition and status management module 12, a transformer power supply group power aggregation and threshold judgment module 13, a power budget calculation module 14, a strategy engine and allocation module 15, and a smooth adjustment and command issuance module 16. The system also includes an alarm and notification module 17, a log and analysis module 18, and a configuration interface module 19.

[0032] The transformer power supply group parameter database 11 establishes data connections with the data acquisition and status management module 12, the transformer power supply group power aggregation and threshold judgment module 13, and the power budget calculation module 14, respectively.

[0033] The transformer power supply group parameter database 11 is used to store and maintain the transformer power supply group-level constraint parameters for each charging station. The transformer power supply group-level constraint parameters define a distribution transformer or a feeder as a transformer power supply group. These parameters include transformer capacity parameters, threshold coefficients, power budget upper limit parameters, scheduling cycle parameters, and strategy selection parameters. The transformer power supply group parameter database 11 also stores a list of charging piles within each transformer power supply group, the status of each charging pile's participation in control switching, the weight parameters of each charging pile, the priority parameters of each charging pile, the rated power parameters of abnormal charging piles, and the deduction parameters for uncontrolled loads.

[0034] The data acquisition and status management module 12 is used to collect and maintain real-time operating data of each charging pile within the transformer power supply group. The real-time operating data includes the electrical operating parameters of the charging piles. The data acquisition and status management module 12 is also used to collect data from the vehicle-side battery management system, and based on the collected data, to generate a set of charging piles that can participate in regulation and a set of charging piles with communication anomalies.

[0035] The transformer power supply group power aggregation and threshold judgment module 13 is used to perform transformer power supply group-level aggregation operations on real-time operating data within the transformer power supply group, and calculate the total power of the transformer power supply group. The module 13 compares the total power of the transformer power supply group with the transformer power supply group-level safety threshold. The module 13 initiates the control process when trigger conditions are met. Trigger conditions include the total power of the transformer power supply group exceeding the transformer power supply group-level safety threshold, the start or end of charging events at charging piles within the transformer power supply group, and communication abnormalities or the arrival of a timing period.

[0036] The power budget calculation module 14 is used to calculate the allocable power of the transformer power supply group under the constraints of the upper limit of the allocable power budget calculation module and the safety threshold of the transformer power supply group. During the calculation process, the power budget calculation module 14 executes deduction rules. The deduction rules are defined as follows: when there is an uncontrolled load, the power occupied by the uncontrolled load is deducted first; when there is a charging pile with communication abnormalities, the conservative power limit of the charging pile with communication abnormalities is deducted first. The power budget calculation module 14 calculates the current time based on the following formula. The power budget that can be allocated to the transformer power supply group :

[0037] ;

[0038] In the formula, Defined as the total physical capacity of the transformer; Defined as the rated operating power of a transformer; Defined as a safety threshold coefficient; Defined as the current time Monitored uncontrolled load power; Defined as a set of charging stations with communication failures; A set of charging stations defined as having communication anomalies The Middle Conservative power reduction for charging stations with communication abnormalities.

[0039] The strategy engine and allocation module 15 are used to allocate power budget in the transformer power supply group. Under the constraints, the target power allocation results of each participating charging pile in the transformer power supply group are calculated and output. The strategy engine and allocation module 15 are configured with a weighted allocation strategy, a priority guarantee strategy, a round-robin power reduction strategy, a differentiated strategy based on battery state of charge, and an on-demand preemption strategy.

[0040] The smoothing adjustment and command issuance module 16 receives the target power allocation result output by the strategy engine and the allocation module 15, and converts the target power allocation result into a power issuance command. The smoothing adjustment and command issuance module 16 applies smoothing constraints to power changes. The smoothing constraints include rate-of-change limiting processing and filtering processing. The smoothing adjustment and command issuance module 16 sends the power issuance command to the charging pile or station control gateway via a communication link, driving the charging pile to perform power adjustment.

[0041] See attached document Figure 1 The calculation method for the available and allocable power budget calculation module based on a robust deduction mechanism provided in this invention relies on the definition and construction of a transformer power supply group model. The transformer power supply group model first establishes a mapping relationship between logical groups and physical power supply equipment, and then calculates the baseline safety threshold power based on physical parameters. The transformer power supply group power aggregation and threshold judgment module 13 uses the total physical capacity of the transformer, the rated operating power of the transformer, and the safety threshold coefficient to determine the baseline safety threshold power according to the following formula. :

[0042] ;

[0043] In the formula, Defined as the total physical capacity of the transformer; Defined as the rated operating power of a transformer; Defined as a safety threshold coefficient; Defined as the calculated baseline safety threshold power. The system establishes the physical power boundary of the current logic transformer power supply group by taking the smaller value between the total physical capacity of the transformer and the converted rated operating power.

[0044] The transformer power supply group model also defines classification attributes for uncontrolled and controlled loads. The system registers lists of uncontrolled load devices and controlled charging pile devices within the logical transformer power supply group. The list of uncontrolled load devices includes lighting equipment, air conditioning equipment, and other ancillary facilities; the power consumption of these devices is marked as a non-adjustable component. The list of controlled charging pile devices includes all DC or AC charging piles for electric vehicles within the transformer power supply group that support power regulation commands; the power consumption of these devices is marked as an adjustable component.

[0045] The calculation method for the available and allocable power budget based on a robust deduction mechanism provided by this invention includes deduction logic for abnormal and uncontrolled factors, which is executed by the power budget calculation module 14. The power budget calculation module 14 determines the power values ​​that cannot participate in allocation at the current moment through the deduction logic, thereby preventing uncontrollable or unmeasurable power capacity from being incorrectly included in the allocable budget.

[0046] The power budget calculation module 14 first performs the identification and deduction operation of uncontrolled load power. Uncontrolled load power originates from electrical equipment within the charging station other than controlled charging piles. The power budget calculation module 14 calculates the uncontrolled load power by subtracting the real-time power values ​​of all online controlled charging piles from the total meter power value. As an alternative implementation, the power budget calculation module 14 directly obtains the uncontrolled load power by reading data from independent metering instruments connected to the uncontrolled load circuit. The power budget calculation module 14 defines the obtained uncontrolled load power as... ,in This represents the current moment of sampling.

[0047] The power budget calculation module 14 then performs a conservative deduction operation for charging piles with communication abnormalities. The data acquisition and status management module 12 monitors the communication connection status of each charging pile within the transformer power supply group in real time. When the data acquisition and status management module 12 determines that the communication heartbeat of a specific charging pile has been interrupted or the data packet has been lost for more than a preset time limit, the data acquisition and status management module 12 marks the specific charging pile as a charging pile with communication abnormalities and adds it to the set of charging piles with communication abnormalities. .

[0048] Power budget calculation module 14 is for communication anomaly set For each charging station experiencing a communication malfunction, a conservative power limit is assigned. Since the system cannot obtain the real-time actual output power of the charging station with the communication malfunction, the power budget calculation module 14 forcibly sets the current power occupancy value of the charging station with the communication malfunction to a preset conservative power limit. Conservative power rating The value is set to the rated power value on the device nameplate of the charging pile with communication abnormalities.

[0049] The power budget calculation module 14 calculates the unavailable capacity occupancy value within the transformer power supply group at the current moment, based on the uncontrolled load power and the conservative rated power of all charging piles with communication anomalies. The calculation formula is as follows:

[0050] ;

[0051] In the formula, Defined as the current time Unavailable capacity occupancy value within the transformer power supply group; Defined as the current time Uncontrolled load power; Defined as a set of communication anomaly stubs; Defined as an index variable in the set; Defined as the first The conservative power limit for each charging station with communication issues.

[0052] After calculating the unavailable capacity occupancy value within the transformer power supply group, the power budget calculation module 14 executes the uncontrollable boundary judgment logic. The power budget calculation module 14 then calculates the unavailable capacity occupancy value within the group. Reference safety threshold power of transformer group Comparison. When The value is greater than or equal to When the value is reached, the power budget calculation module 14 determines that the current system has entered an uncontrollable boundary state. In this uncontrollable boundary state, the power budget calculation module 14 generates a stop automatic control command and sends it to the strategy engine and allocation module 15. Simultaneously, the power budget calculation module 14 generates a capacity over-limit alarm signal.

[0053] Further, the power budget calculation module 14 performs the step of calculating the allocable power of the transformer power supply group. The power budget calculation module 14 then performs the remaining capacity calculation. The power budget calculation module 14 subtracts the real-time monitored uncontrolled load power from the maximum total load baseline, and further subtracts the conservative allowable power of all charging piles with communication anomalies. The power budget calculation module 14 applies non-negative constraint logic to perform boundary correction on the calculation results, and calculates the current time based on the aforementioned transformer power supply group allocable power budget calculation formula. The power budget that can be allocated to the transformer power supply group This budget value serves as a hard constraint upper limit for subsequent policy engines.

[0054] Power budget calculation module 14 calculates the group allocatable power budget. The value is passed as an output parameter to the strategy engine and allocation module 15. The strategy engine and allocation module 15 use this value as a hard constraint upper limit on the sum of the target power of all controlled charging piles within this scheduling cycle. When the value equals zero, the strategy engine and allocation module 15 generate a power limiting command and send it to all controlled charging piles until the next cycle calculates the power limit. Greater than zero. Through the above calculation process, the system ensures that the total power sent to the controlled charging piles at any given time, plus the power occupied by the uncontrolled loads and abnormal charging piles, is strictly within the safe operating boundary of the transformer power supply group.

[0055] See attached document Figure 2 The multi-strategy power allocation engine provided by this invention is specifically implemented by the strategy engine and the allocation module 15. The strategy engine architecture adopts a modular configuration approach, aiming to map the allocable power budget of the transformer power supply group to the target power command for a single charging pile. The strategy engine and allocation module 15 are configured to receive allocable power budget data of the transformer power supply group from the power budget calculation module 14, and receive real-time status and vehicle demand data of each charging pile from the data acquisition and status management module 12, ultimately outputting a single-pile power allocation command that meets the constraints to the smooth adjustment and command issuance module 16.

[0056] The strategy engine and allocation module 15 internally includes a strategy selection unit, a parameter parsing unit, a multi-strategy algorithm library, and an output verification unit. The strategy selection unit activates a unique computational logic path from the multi-strategy algorithm library based on the read strategy selection parameters. The multi-strategy algorithm library contains weighted allocation logic, priority guarantee logic, round-robin logic, and differential logic based on battery state of charge.

[0057] All activation strategies in the multi-strategy algorithm library must adhere to a unified global constraint model. This global constraint model defines the convergence boundary of the allocation results, ensuring that the total power allocated to all controlled charging piles is strictly less than or equal to the allocatable power budget of the input transformer power supply group. The strategy engine and allocation module 15 perform allocation calculations based on the following global constraint formula:

[0058] ;

[0059] In the formula, Defined as the set of charging piles that are currently online and participating in regulation; Defined as the index of the charging station in the set; Defined as the first calculated by the strategy engine The charging station at the current moment Target power allocation; Defined as the power budget that can be allocated to the transformer power supply group at the current moment, input by the power budget calculation module 14. This formula ensures that, regardless of the specific allocation strategy adopted, the total power command output by the system is always controlled by the remaining available capacity of the transformer.

[0060] The output verification unit is used to perform device-level physical constraint verification on the preliminary results calculated by the multi-strategy algorithm library. The output verification unit stores the minimum physical operating power of each charging pile. and the maximum physical output power of the hardware The output verification unit simultaneously reads the power demand requested by the vehicle's battery management system. The output verification unit operates according to the following boundary conditions. Final revisions to be made:

[0061] ;

[0062] The output verification unit detects that the preliminary calculation result is lower than the hardware's physical minimum operating power. At that time, the target power will be allocated. Forced to zero or .

[0063] See attached document Figure 2 The multi-strategy power allocation strategy engine provided by the present invention supports the switching and execution of various specific strategies. The strategy engine and the allocation module 15 select one or more combinations of the following strategies, priority sequence allocation strategies, or battery status response strategies according to the strategy configuration parameters in the transformer power supply group parameter database 11.

[0064] When executing the capacity-following allocation strategy, the strategy engine and allocation module 15 employs proportional scaling logic based on vehicle power demand. The strategy engine and allocation module 15 first calculates the total power demand of all controlled charging piles within the transformer power supply group at the current moment, and then compares this total with the allocable power budget of the transformer power supply group. The comparison is performed. When the total demand power is less than or equal to the group's allocable power budget, the strategy engine and allocation module 15 directly set the target power of each charging pile to the vehicle's demand power for that charging pile. When the total demand power is greater than the transformer power supply group's allocable power budget, the strategy engine and allocation module 15 activates congestion control logic, allocating the budget according to the proportion of each charging pile's demand power to the total demand power. The strategy engine and allocation module 15 utilizes weighting coefficients... The allocation ratio is adjusted, and the weighting coefficient of all charging stations is adjusted under the default mode that only considers capacity following. Set to 1. The strategy engine and allocation module 15 calculate the first [unit / item] according to the following formula. The target power of each charging pile :

[0065] ;

[0066] In the formula, Defined as the first The charging station at the current moment Reported vehicle power requirements; Defined as the power budget that can be allocated to the transformer power supply group at the current moment; Defined as the set of charging piles currently involved in regulation; and Defined as the weight adjustment coefficient for the corresponding charging pile; The summation index is used within the set. This formula ensures that when transformer capacity is insufficient, all charging vehicles can fairly allocate available power resources according to their demand, and the allocation result of any single charging pile will not exceed its physical demand limit.

[0067] When executing the priority sequence allocation strategy, the strategy engine and allocation module 15 employs a sorting-based, step-by-step deduction logic. The strategy engine and allocation module 15 reads the priority identifier of each charging pile from the transformer power supply group parameter database 11. The strategy engine and allocation module 15 then allocates the set of charging piles participating in the regulation. The charging piles are rearranged according to their priority from highest to lowest to generate an ordered queue. The strategy engine and allocation module 15 then sequentially satisfy the power requirements of each charging pile according to the order of the ordered queue. For the current charging pile in the queue, the strategy engine and allocation module 15 set the target power to the smaller of the charging pile's required power and the current remaining budget power. After determining the target power of the current charging pile, the strategy engine and allocation module 15 deducts the target power from the remaining budget power and passes the updated remaining budget power to the next charging pile in the queue. When the remaining budget power reaches zero, the target power of subsequent unallocated charging piles in the queue is forcibly set to zero or the minimum maintenance power.

[0068] When executing the battery state response strategy, the strategy engine and allocation module 15 employs differentiated weighted logic based on the battery state of charge (SOC). The strategy engine and allocation module 15 acquires real-time SOC data of vehicles connected to each charging station through the data acquisition and state management module 12. The strategy engine and allocation module 15 has preset SOC segmentation thresholds and corresponding weight mapping tables. When the vehicle's battery SOC is lower than the preset low-charge threshold, the strategy engine and allocation module 15 assigns a higher weight adjustment coefficient to that charging station. When the vehicle's battery state of charge is higher than a preset high charge threshold, the strategy engine and allocation module 15 assign a lower weight adjustment coefficient to the charging station. The strategy engine and allocation module 15 substitute the determined weight adjustment coefficients into the aforementioned capacity-following allocation formula for calculation. This strategy enables vehicles in a low-battery state to obtain a larger allocation ratio when power resources are scarce, thereby shortening their waiting time in the low-battery range.

[0069] The strategy engine and allocation module 15 are also configured with polling and hold logic to handle extremely congested scenarios. This applies when the transformer power supply group has an allocable power budget. When the power output of a single charging station, calculated using proportional allocation, is extremely low, falling below the minimum operating starting power of the charging station, the strategy engine and allocation module 15 automatically switch to a round-robin mode. In round-robin mode, the strategy engine and allocation module 15 divide the time axis into several fixed-length time slices. Within each time slice, the strategy engine and allocation module 15 selects only a subset of charging stations to allow power output, while the remaining charging stations remain in standby mode. The strategy engine and allocation module 15 rotates the selected set of charging stations between adjacent time slices, ensuring that all connected vehicles receive intermittent charging services within the statistical period.

[0070] See attached document Figure 2 The multi-strategy power allocation engine provided by this invention adopts a unified strategy target power calculation paradigm to ensure that the calculation of the target power of a single pile can meet the hard constraint of transformer capacity under different strategy modes. The strategy target power calculation formula is executed by the strategy engine and the allocation module 15.

[0071] The strategy engine and allocation module 15 first defines the comprehensive weight coefficient of a single pile. The overall weighting coefficient It is a normalized, dimensionless value determined by the currently active policy logic. In the capacity-following allocation policy, It is uniformly set to 1; in priority protection strategies or battery status response strategies. The value is dynamically assigned based on a preset priority list or a battery state-of-charge segmentation mapping table. The strategy engine and allocation module 15 use this coefficient to adjust the ability of each charging pile to acquire power resources in the competition for power resources.

[0072] Strategy Engine and Allocation Module 15: Allocable Power Budget Based on Transformer Power Supply Group and the vehicle power requirements of each charging station Combined with comprehensive weighting coefficient Execute single pile target power The calculation is performed to simultaneously satisfy both the limits of not exceeding vehicle demand and not exceeding the allocation budget. The strategy engine and allocation module 15 use the same allocation formula structure as in the aforementioned embodiments, the difference being the incorporation of dynamically changing comprehensive weight coefficients. This calculation logic ensures that the allocation result neither results in power waste nor exceeds transformer limits.

[0073] After completing the above calculations, the strategy engine and allocation module 15 also need to perform minimum operating power constraint verification on the calculation results. The strategy engine and allocation module 15 reads the minimum physical operating power of each charging pile. When the calculation yields Less than If the power is greater than 0, the strategy engine and allocation module 15 determine that the power cannot maintain the stable operation of the charging module. At this time, the strategy engine and allocation module 15 execute low-power cutoff logic, reducing the target power of the charging pile. The forced correction to 0 means issuing a pause charging command and recovering the released power quota into the transformer power supply group's allocable power budget for the next iteration or keeping it as redundancy.

[0074] The strategy engine and allocation module 15, through the above calculation paradigm, ensure that at any given time... The total target power of all controlled charging piles satisfies the aforementioned global constraint conditions.

[0075] The strategy engine and allocation module 15 will calculate and verify the final result. The sequence is transmitted as an output signal to the smoothing adjustment and command issuance module 16. The smoothing adjustment and command issuance module 16 generates the final control command based on the target power sequence.

[0076] The power command smoothing adjustment technology provided by this invention includes a power mutation analysis step, which is executed by the smoothing adjustment and command issuance module 16. The smoothing adjustment and command issuance module 16 is located at the output of the strategy engine and the allocation module 15, and is used to quantify the magnitude and rate of power change before converting discrete target power values ​​into physical control signals.

[0077] The smooth adjustment and instruction issuance module 16 first receives instructions from the policy engine and the allocation module 15 during the current scheduling period. The output is the target power sequence for a single pile. Simultaneously, the smoothing adjustment and command issuance module 16 reads the previous scheduling cycle from its local storage unit. The historical values ​​of the power commands actually issued to each charging pile. The smooth adjustment and command issuance module 16 establishes a mapping relationship between the power values ​​of two adjacent scheduling cycles, aiming to identify step changes whose amplitude exceeds the hardware's capacity.

[0078] The smoothing adjustment and command issuance module 16 performs power command deviation calculation for each charging pile participating in the regulation. The smoothing adjustment and command issuance module 16 defines the power command deviation as the algebraic difference between the target power at the current moment and the issued power at the previous moment. This calculation process reveals the magnitude of the power output adjustment required by the system for the charging pile under discrete time slices. The smoothing adjustment and command issuance module 16 calculates the first... The charging station at the current moment Power command mutation amplitude :

[0079] ;

[0080] In the formula, Defined as the strategy engine and allocation module 15 at the current moment The output of the first The target power allocation for each charging station; Defined as smooth adjustment and command issuance module 16 at time Finally to the The execution power command issued by each charging pile; Defined as the amplitude of unfiltered power command jumps. Calculated by the smoothing adjustment and command issuance module 16. It includes positive and negative values. Positive values ​​represent power increase requests, and negative values ​​represent power decrease requests.

[0081] The smoothing adjustment and command issuance module 16 then executes the power surge detection logic. The smoothing adjustment and command issuance module 16 has a preset safe rate of change threshold. Safety change rate threshold Defined as the maximum power change rate allowed by the charging pile hardware circuit and vehicle battery management system, its unit is kilowatts per second (kW / s). The smooth adjustment and command issuance module 16 combines the system scheduling cycle length. Calculate the maximum safe step size allowed within a single cycle.

[0082] The smoothing adjustment and command issuance module 16 compares the absolute value of the calculated power command mutation amplitude with the maximum safe step size. When the absolute value of the power command mutation amplitude exceeds the maximum safe step size, the smoothing adjustment and command issuance module 16 determines that the current command has a power mutation risk. This determination logic is based on the following inequality relationship:

[0083] ;

[0084] In the formula, This indicates the absolute value operation; Defined as a preset safety change rate threshold; Defined as the time interval between two consecutive scheduling commands. When the above inequality holds, the smoothing adjustment and command issuance module 16 identifies direct issuance. This will cause the transient rate of change of the charging pile output current to exceed the physical safety boundary, thereby causing DC bus voltage fluctuations or triggering the overcurrent protection mechanism on the vehicle side.

[0085] The smoothing adjustment and command issuance module 16 also analyzes the impact of power surges on the transformer side. When multiple charging piles within the transformer power supply group simultaneously experience power surges in the same direction, and the sum of the surge amplitudes exceeds a preset percentage of the transformer's rated capacity, the smoothing adjustment and command issuance module 16 determines that there is a transformer power supply group-level surge risk. The smoothing adjustment and command issuance module 16 further analyzes the impact of power surges on the transformer side by analyzing all... The charging stations are marked, generating a set of adjustments that requires smoothing. This set serves as the input for subsequent filtering or slope limiting processes, ensuring that the final issued commands exhibit continuous and gradual changes in the time domain.

[0086] The power command smoothing adjustment technology provided by this invention includes a smoothing control algorithm, which is executed by the smoothing adjustment and command issuance module 16. After identifying the risk of power mutation, the smoothing adjustment and command issuance module 16 uses slope limiting logic to shape the original target power sequence and generate the final execution command that conforms to the hardware physical constraints.

[0087] The smoothing adjustment and command issuance module 16 first determines the maximum allowable power change step size for the current scheduling cycle. The smoothing adjustment and command issuance module 16 reads the preset power ramp rate limit value from the system configuration storage unit. This rate limit is set based on the dynamic response characteristics of the charging pile power module and the grid's specifications for load fluctuation. The smoothing adjustment and command issuance module 16 combines the scheduling cycle length... The maximum allowable step size is calculated using the following formula. :

[0088] ;

[0089] In the formula, Defined as the maximum allowable increase or decrease in the output power of a charging pile within a single scheduling cycle; Defined as the power ramp rate limit, in kilowatts per second; Defined as the time interval between two consecutive instruction issuance operations, in seconds.

[0090] The smoothing adjustment and command issuance module 16 then performs command correction calculations based on interval constraints. The smoothing adjustment and command issuance module 16 reads the power command actually issued in the previous scheduling cycle. and the target power output by the current strategy engine The smooth adjustment and command issuance module 16... With the reference center, Using the radius, construct the safe power allowable range for the current moment. The smooth adjustment and command issuance module 16 will target the power. The power is forcibly constrained within the safe power allowable range.

[0091] The smooth adjustment and command issuance module 16 calculates the following smooth control formula: The charging station at the current moment The final execution power command :

[0092] ;

[0093] In the formula, Defined as the final message sent to the first after smoothing. The execution power command for each charging pile; Defined as the execution power instruction issued in the previous moment; Defined as the maximum permissible step size; Defined as the raw target power calculated by the strategy engine. This formula is passed through the inner layer. The function limits the increase in power to no more than And through the outer layer The function limits the decrease in power to no more than This allows for bidirectional slope control.

[0094] The smooth adjustment and command issuance module 16 calculates... Then, the command issuance and status update operations are performed. The smooth adjustment and command issuance module 16 transmits the data through the communication interface. The command is sent to the underlying controller of the corresponding charging pile. Simultaneously, the smooth adjustment and command issuance module 16 will... Write to the historical state buffer queue to replace It participates in the smoothing calculation of the next scheduling cycle. Through the above iterative process, the system ensures that the output power curve of the charging pile exhibits continuous and stable variation characteristics in the time domain, eliminating the risks of grid impact and equipment loss caused by step response.

[0095] The power command smoothing adjustment technology provided by this invention includes a command issuance closed-loop step, which is jointly executed by the smoothing adjustment and command issuance module 16 and the data acquisition and status management module 12. The command issuance closed-loop step aims to verify the consistency of the physical device's response to control commands and provide accurate status feedback for decision-making in the next scheduling cycle.

[0096] The smoothing adjustment and command issuance module 16 calculates the final execution power command. Then, the protocol encapsulation and transmission operations are performed first. The smoothing adjustment and command issuance module 16 converts the numerical power command into a communication message recognizable by the underlying controller according to a preset communication protocol template. The protocol template includes a Modbus register address mapping or a charging configuration message body for the OCPP protocol. The smoothing adjustment and command issuance module 16 transmits the command to the first-level controller via the communication bus. The controller of each charging pile sends a write operation command and waits for the device's response confirmation frame within a preset communication timeout window. Once the device's response confirmation frame is received, the smooth adjustment and command issuance module 16 determines that the command issuance process is complete.

[0097] The data acquisition and status management module 12 then performs real-time monitoring of the instruction execution effect. The data acquisition and status management module 12 reads the data at a sampling rate higher than the scheduling frequency. The actual output power of each charging pile The data acquisition and status management module 12 will display the actual output power. The execution power command issued by the smooth adjustment and command issuance module 16 Compare the data and calculate the current tracking deviation value.

[0098] The data acquisition and status management module 12 calculates the data based on the following formula. The charging station at the current moment Power tracking deviation :

[0099] ;

[0100] In the formula, Defined as the first The charging station at the current moment The absolute value of the power tracking deviation; Defined as the expected execution power issued by the system; Defined as the actual output power collected by the sensor; This indicates the operation of taking the absolute value.

[0101] The data acquisition and status management module 12 uses power tracking deviation to execute response status determination logic. The data acquisition and status management module 12 has a preset allowable steady-state deviation threshold. and response delay tolerance time When the duration after the command is issued exceeds And power tracking deviation Continuously exceeding the allowable steady-state deviation threshold At that time, the data acquisition and status management module 12 determines that the charging pile is in a state of command synchronization failure.

[0102] Upon determining that a charging pile is in a command synchronization failure state, the data acquisition and status management module 12 immediately performs status degradation processing. The module modifies the charging pile's operating status flag to "communication abnormal" or "controlled failure." This status flag change is directly fed back to the transformer power supply group parameter database 11. In the calculation process of the next scheduling cycle, the power budget calculation module 14, based on the updated status flag, removes the charging pile from the set of charging piles participating in the regulation. Its power is conservatively processed according to the abnormal and uncontrolled factors deduction logic of Example 2.

[0103] The data acquisition and status management module 12 also feeds back the success rate statistics of instruction execution to the strategy engine and allocation module 15. When a specific charging pile has a large tracking deviation but does not trigger a fault shutdown in multiple consecutive scheduling cycles, the strategy engine and allocation module 15 automatically reduces the weight adjustment coefficient of the charging pile in subsequent allocation calculations, thereby reducing the allocation of large power quotas to slow-responding devices and ensuring the fast response characteristics and closed-loop stability of the entire charging station power regulation system.

[0104] See attached document Figure 3 This invention provides a dynamic power scheduling method for charging piles oriented towards transformer capacity constraints. This method is executed by a system comprising a transformer power supply group parameter database 11, a data acquisition and status management module 12, a power budget calculation module 14, a strategy engine and allocation module 15, and a smoothing adjustment and command issuance module 16. The method includes a data acquisition step, a transformer power supply group allocable power calculation step, a multi-objective power allocation step, and a power command smoothing and output step.

[0105] The data acquisition and status management module 12 first executes the data acquisition step. The module periodically reads the real-time physical parameters of the transformer power supply group and the operating status data of each charging pile through the sensor network and communication bus. The real-time physical parameters include the transformer's total load current, total transformer voltage, and ambient temperature. The operating status data includes charging pile online signals, fault alarm codes, vehicle connection status confirmation signals, and voltage and current values ​​requested by the vehicle's battery management system. The data acquisition and status management module 12 filters all acquired data and stores it in the group parameter database 11, while also updating the controlled status flags of the charging piles within the group in real time.

[0106] The power budget calculation module 14 then executes the step of calculating the allocable power of the transformer power supply group. The power budget calculation module 14 retrieves the total physical capacity parameters and safety threshold coefficients of the transformer from the transformer power supply group parameter database 11. The power budget calculation module 14 identifies the power consumed by the uncontrolled load at the current moment and identifies the conservative power quota occupied by the charging pile with communication failure. The power budget calculation module 14 subtracts the power of the uncontrolled load and the conservative power of the charging pile with communication failure from the total physical capacity of the transformer to calculate the net available power budget specifically for the controlled charging pile. The power budget calculation module 14 calculates the current moment's allocable power budget according to the aforementioned formula for calculating the allocable power budget of the group. The power budget that can be allocated to the transformer power supply group .

[0107] The strategy engine and allocation module 15 then executes the multi-objective power allocation step. The strategy engine and allocation module 15 receives the allocable power budget for the transformer power supply group. The strategy engine and allocation module 15 reads the currently active allocation strategy configuration of the system. The allocation strategy configuration specifies that the system should execute one of the following logics: capacity following logic, priority sequence logic, and battery status response logic. The strategy engine and allocation module 15 obtains the vehicle power demand and corresponding weight coefficient for each charging pile in a controlled state. The strategy engine and allocation module 15 calculates the strategy target power for each controlled charging pile and ensures that the sum of the strategy target power of all controlled charging piles is strictly less than the allocable power budget of the transformer power supply group. The strategy engine and allocation module 15 performs allocation calculations according to the aforementioned global constraint formula.

[0108] The smoothing adjustment and command issuance module 16 performs the final power command smoothing and output steps. The smoothing adjustment and command issuance module 16 receives the strategy target power sequence output by the strategy engine and allocation module 15. The smoothing adjustment and command issuance module 16 reads the actual power execution command issued to each charging pile in the previous scheduling cycle. The smoothing adjustment and command issuance module 16 calculates the difference between the current strategy target power and the power execution command from the previous time. When the difference exceeds the preset maximum safety step size, the smoothing adjustment and command issuance module 16 applies slope limiting processing to the strategy target power to generate the final power execution command. The smoothing adjustment and command issuance module 16 sends the final power execution command to the underlying controller of each charging pile through the communication interface, completing a single scheduling cycle.

[0109] The dynamic power scheduling method for charging piles provided by this invention adopts a dual-mode driving mechanism that combines periodic clock triggering and asynchronous event triggering. The data acquisition and status management module 12, as the sensing front end of the system, is responsible for monitoring the changes in the system clock signal and power parameters in real time, and determining whether to generate a trigger signal based on the monitoring results to start the recalculation process of the power budget calculation module 14 and subsequent modules.

[0110] The data acquisition and status management module 12 first executes the periodic clock trigger logic. The data acquisition and status management module 12 is internally configured with a system timer, which has a fixed global scheduling cycle. When the system timer's count reaches... At this time, the data acquisition and status management module 12 forcibly generates a global scheduling trigger signal. This periodic clock trigger mechanism ensures that the system can still refresh the power commands of each charging pile at fixed time intervals under stable load and no sudden events, so as to eliminate control errors caused by communication packet loss or equipment clock drift accumulation and maintain the steady-state synchronization of the system.

[0111] The data acquisition and status management module 12 executes asynchronous event triggering logic in parallel to respond to discrete state change events. The module scans in real time for connection confirmation signals, fault alarm signals, and emergency stop signals of all charging piles within the transformer power supply group. When it detects a reversal in the vehicle connection status of any charging pile from disconnected to connected or from connected to disconnected, or when it detects a fault shutdown code reported by any charging pile, the data acquisition and status management module 12 determines that a topology change event has occurred. Upon detecting the topology change event, the module immediately ignores the current system timer count and forcibly generates a global scheduling trigger signal to ensure that newly connected vehicles can promptly obtain power allocation or that power occupied by faulty equipment can be immediately recovered.

[0112] The data acquisition and status management module 12 further executes power fluctuation triggering logic based on analog thresholds. The data acquisition and status management module 12 caches a snapshot of the system state at the current moment after the last successful execution of scheduling calculations; this snapshot includes the uncontrolled load power at the previous moment. And the sum of the power demands of all vehicles at the previous moment. The data acquisition and status management module 12 reads the current uncontrolled load power at a sampling frequency higher than the global scheduling cycle. and the sum of the power demands of all vehicles at the current moment. .

[0113] The data acquisition and status management module 12 calculates the power fluctuation amplitude at the current time relative to the previous scheduling time, and compares this amplitude with a preset dead zone threshold. The data acquisition and status management module 12 determines whether to activate the recalculation process based on the following trigger criterion formula:

[0114] ;

[0115] In the formula, Defined as the current time The trigger status flag bit, Indicates triggering, Indicates to remain; Defined as the uncontrolled load power at the current sampling moment; Defined as the uncontrolled load power during the last execution of scheduling calculations; Defined as the algebraic sum of the power demand of all vehicles in the transformer power supply group at the current sampling time; Defined as the algebraic sum of the power demand of all vehicles in the transformer power supply group at the time of the last scheduling calculation; Defined as a preset power fluctuation dead zone threshold; This indicates the operation of taking the absolute value.

[0116] The data acquisition and status management module 12 uses the above formula to filter out minor sensor noise and battery current ripple interference. When Set as At that time, the data acquisition and status management module 12 sends a start signal to the power budget calculation module 14 and simultaneously updates the data. At the current moment, the status snapshot is updated to the current data, which serves as the benchmark for the next determination and reset. Through this mechanism, the system can quickly adjust the allocation strategy when the transformer background load fluctuates significantly or multiple electric vehicles simultaneously request a change in charging stage (such as from constant current to constant voltage), preventing transformer overload or idle power resources.

[0117] The cyclic scheduling mechanism provided by this invention is led by the data acquisition and state management module 12, and jointly executed by the power budget calculation module 14, the strategy engine and allocation module 15, and the smooth adjustment and command issuance module 16. This mechanism ensures that the system operates strictly according to the timing logic of sampling, calculation, issuance, and waiting in discrete time slices, guaranteeing data consistency and the timeliness of control commands.

[0118] Upon receiving a periodic clock trigger signal or an asynchronous event trigger signal, the data acquisition and status management module 12 performs a status lock operation. The module freezes all real-time data in the transformer power supply group parameter database 11 at the current moment, generating a unique input state vector. Input state vector This includes freezing the transformer load data at the current moment, the connection status of all charging piles, vehicle power demand, and fault flags. Throughout subsequent calculations in this scheduling cycle, even if the external physical environment changes, the data source referenced by the module's internal processing remains constant. This is to eliminate computational logic conflicts caused by asynchronous data updates.

[0119] The power budget calculation module 14, the strategy engine and allocation module 15, and the smooth adjustment and command issuance module 16 sequentially process the input state vector. The process is as follows: Power budget calculation module 14 calculates the power budget based on the frozen transformer load; strategy engine and allocation module 15 allocates target values ​​based on the frozen demand power; smoothing adjustment and instruction issuance module 16 calculates smoothed execution instructions based on frozen historical instructions. Intermediate calculation results are transmitted between modules via an internal bus, forming a unidirectional and atomic data processing pipeline.

[0120] After the smooth adjustment and instruction issuance module 16 completes the instruction sending operation, the data acquisition and status management module 12 performs a scheduling cycle time verification. The data acquisition and status management module 12 records the start time of the current scheduling cycle. and the end time The data acquisition and status management module 12 calculates the processing time for this scheduling and compares it with the preset minimum system scheduling cycle. The comparison is performed. The data acquisition and status management module 12 determines the earliest start time of the next scheduling cycle based on the following formula. :

[0121] ;

[0122] In the formula, Defined as the earliest time point at which the system is allowed to initiate the next scheduling calculation; Defined as the trigger lock time of the current scheduling loop; Defined as the moment when the current scheduling cycle instruction is completed; Defined as the minimum scheduling interval time preset by the system, it is used to limit the maximum frequency of instruction issuance and prevent communication bus congestion; Defined as the processor idle protection time, it is used to ensure that the controller has a time window to perform background maintenance tasks between two high-load computing operations.

[0123] The data acquisition and status management module 12 is based on calculations. Configures the system timer's compare register. When the current system time... Less than When the system time is reached, it enters an idle waiting state, responding only to high-priority emergency stop interrupt signals. achieve When this happens, the data acquisition and status management module 12 is released from the waiting state, allowing it to respond to new periodic or event-triggered signals.

[0124] The data acquisition and status management module 12 also performs computation timeout exception monitoring. If the processing time is excessive in a single scheduling loop... Exceeded the preset maximum allowable delay threshold The data acquisition and status management module 12 determines that the current calculation cycle has timed out. The data acquisition and status management module 12 records a timeout fault event and immediately resets the calculation pipeline. If the cumulative number of timeout fault events exceeds the tolerance limit within a preset statistical window, the data acquisition and status management module 12 switches the system to a safety degradation mode. At this time, the strategy engine and allocation module 15 stop complex optimization calculations and instead use a fixed average allocation strategy to directly generate control commands to prioritize the system's real-time response capability.

[0125] This invention provides a power scheduling operation process under normal peak-hour conditions. This process is executed collaboratively by a data acquisition and status management module 12, a power budget calculation module 14, a strategy engine and allocation module 15, and a smooth adjustment and command issuance module 16. This scenario corresponds to a situation where the number of vehicles connected to the charging station is large and the total power demand exceeds the remaining available capacity of the transformer.

[0126] The data acquisition and status management module 12 first detects the current time. The data acquisition and status management module 12 identifies the set of controlled charging piles that are online and charging. The number of members has increased significantly. The data acquisition and status management module 12 reads the vehicle power demand reported by each charging pile within the set. This data is then aggregated and transmitted to the policy engine and allocation module 15. Simultaneously, the data acquisition and status management module 12 obtains the current uncontrolled load power. And transmit it to the power budget calculation module 14.

[0127] The power budget calculation module 14 performs the calculation of the allocable power budget for the transformer power supply group. The power budget calculation module 14 is based on the total physical capacity of the transformer. and safety threshold coefficient Subtracting the current uncontrolled load power And the conservative power allowance for communication anomaly piles. The power budget calculation module 14 outputs the current allocable power budget for the transformer power supply group. Under normal peak-hour conditions, since uncontrolled loads (such as lighting and air conditioning) are in a stable operating state, the power budget that can be allocated to the transformer power supply group is sufficient. It is presented as a finite value strictly constrained by the physical upper limit.

[0128] Strategy Engine and Allocation Module 15: Allocable Power Budget for Receiver Group Power requirements of all charging stations for vehicles The strategy engine and allocation module 15 perform a comparison and judgment of supply and demand. Under normal peak conditions, the system state satisfies the following supply-demand imbalance inequality condition:

[0129] ;

[0130] In the formula, Defined as all charging piles participating in regulation at the current moment The total power demand of the vehicles; Defined as the current time The transformer power supply group has an allocable power budget. The validity of this inequality indicates that the system has entered a power-constrained allocation mode.

[0131] The strategy engine and allocation module 15 then activates the weighted compression allocation logic. The strategy engine and allocation module 15 determines the comprehensive weight coefficient of each charging pile according to the currently configured strategy mode (such as a capacity-following strategy). The strategy engine and allocation module 15 utilizes the calculation paradigm of Embodiment 3 to calculate the strategic target power for each charging pile. In this scenario, the calculation result will inevitably lead to... This means that the allocated power received by each charging station is less than its requested power. The strategy engine and allocation module 15 ensure that all calculated power is less than the allocated power. The sum is exactly equal to or slightly less than This maximizes the use of power resources while ensuring that the transformer is not overloaded.

[0132] The smoothing adjustment and command issuance module 16 receives the compressed policy target power sequence. The smoothing adjustment and command issuance module 16 will then... Compared with the execution instructions of the previous moment A comparison is performed. If the allocation ratio changes abruptly due to the access of a new vehicle, the smoothing adjustment and command issuance module 16, based on the smoothing control algorithm of Embodiment 4, limits the slope of the power decrease and generates the final execution power command. The smooth adjustment and command issuance module 16 sends commands to each charging pile through the communication interface, controlling each charging pile to reduce its output current, so that the total load curve of the entire charging station operates close to the upper limit of the transformer's safe capacity, until some vehicles are fully charged and leave the site or the total demand drops to within the budget range.

[0133] The power scheduling operation process provided by this invention focuses on describing the emergency response mechanism when the system detects a communication interruption of the charging pile or a sudden increase in uncontrolled load. This process is executed collaboratively by the data acquisition and status management module 12, the power budget calculation module 14, the strategy engine and allocation module 15, and the smooth adjustment and command issuance module 16.

[0134] The data acquisition and status management module 12 performs anomaly monitoring and status determination steps. Within each communication cycle, the data acquisition and status management module 12 checks the handshake signals with the underlying controllers of each charging pile. When the data acquisition and status management module 12 continuously... No message was received within the communication cycle. When a charging pile sends a heartbeat feedback or data message, or when the CRC check of the received message continues to fail, the data acquisition and status management module 12 determines the first... One charging station experienced a communication interruption.

[0135] The power budget calculation module 14 then performs a conservative power deduction calculation, and calculates the safe available power budget under abnormal scenarios according to the following formula. :

[0136] ;

[0137] In the formula, Defined as the moment the exception occurs. The remaining available power budget for normal charging stations; Defined as the transformer safety threshold coefficient; Defined as the total physical capacity of the transformer; Defined as the uncontrolled load power measured at the current moment; Defined as the set of charging stations currently identified as having communication anomalies or malfunctions; Defined as the first in the set The physical rated maximum power of each charging station.

[0138] The power budget calculation module 14 physically isolates the uncontrollable risk power space through the above calculations. If the calculation results... If the value is less than zero, the power budget calculation module 14 forces the value to be zero. At this point, because the power budget calculation module 14 has deducted the zero value... The remaining budget for normal charging stations will be significantly reduced.

[0139] The strategy engine and allocation module 15 receive the updated and the remaining normal charging piles The list of requirements. The strategy engine and allocation module 15 re-run the allocation algorithm under the new tight budget constraints. Based on the weight ratio of each normal charging station, the strategy engine and allocation module 15 reallocate the limited remaining power to... The members in the process. This process results in the normal power distribution of charging stations. Forced to descend in order to make room for the full load risk that would result from abnormal piles.

[0140] The smoothing and command issuance module 16 executes emergency command issuance. The smoothing and command issuance module 16 receives a new target power sequence and identifies it as an emergency dispatch triggered by a fault. The smoothing and command issuance module 16 temporarily bypasses the rate-of-decrease limits in the regular smoothing constraint logic, allowing the power command to decrease at the maximum physical slope allowed by the system. The smoothing and command issuance module 16 quickly issues the reduced power command... The message is sent to all working charging stations. Through this process, the system responds to fault risks within a single scheduling cycle, ensuring that even in the event of communication loss, the total transformer load remains within a safe threshold. under.

[0141] See attached document Figure 4 The present invention provides an electronic device 100 capable of executing the above-described dynamic power scheduling method for charging piles oriented towards transformer capacity constraints. The electronic device 100 physically includes a processor 101, a memory 102, a communication interface 103, and a bus 104.

[0142] Processor 101 executes the dynamic power scheduling methods for charging piles in Embodiments 5 and 6 by reading computer program code stored in memory 102. Processor 101 is configured to perform logical operations including data acquisition, allocable power budget calculation module calculation, strategy allocation, and instruction smoothing. Specifically, processor 101 periodically acquires transformer load data collected by external sensors and status data reported by each charging pile through communication interface 103. Processor 101 uses its internal arithmetic logic unit to execute the allocable power budget calculation formula for the transformer power supply group in Embodiment 2, deducting the real-time monitored uncontrolled load power and the conservative power of abnormal piles from the total physical capacity of the transformer to obtain the net available power budget at the current moment.

[0143] The processor 101 further allocates power quotas to the charging piles in the controlled state according to the preset allocation strategy configured in the memory 102. The processor 101 executes the multi-strategy in Embodiment 3, calculates the target power of each charging pile, and verifies that the sum of all target powers is less than or equal to the net available power budget. Subsequently, the processor 101 executes the smooth control algorithm in Embodiment 4, calculates the difference between the current instruction and the previous instruction, and corrects the instruction according to the preset ramp rate limit value to generate the final execution power instruction.

[0144] Communication interface 103 is used to establish a data channel between electronic device 100 and external hardware entities. Communication interface 103 is physically connected to the transformer monitoring instrument and the underlying controller of each charging pile. Communication interface 103 supports Modbus-RTU, TCP / IP, or CAN bus communication protocols. Processor 101 sends the calculated final execution power command to the corresponding charging pile controller through communication interface 103, and receives the execution confirmation frame and the actual output power sample value fed back by the charging pile controller.

[0145] The present invention also provides a computer-readable storage medium, which is a non-volatile storage medium. The computer-readable storage medium stores computer program instructions. When the computer program instructions are executed by the processor 101 of the electronic device 100, the processor 101 causes the processor 101 to execute the dynamic power scheduling method for charging piles oriented towards transformer capacity constraints in the above embodiments.

Claims

1. A dynamic power scheduling method for charging piles oriented towards transformer capacity constraints, characterized in that, Includes the following steps: The data acquisition and status management module collects real-time physical parameters of the transformer group and real-time operating data of each charging pile in the group, obtains the uncontrolled load power and performs non-negative or upper limit constraint logic correction on the obtained results, and generates a set of charging piles that can participate in regulation and a set of charging piles with communication abnormalities based on the communication connection status. Under the constraints of the total physical capacity of the transformer and the group-level safety threshold, the power budget calculation module subtracts the uncontrolled load power from the total physical capacity benchmark of the transformer, and further subtracts the conservative quota power of all charging piles in the set of charging piles with communication abnormalities, to calculate the group-allocable power budget at the current moment. The strategy engine and allocation module receive the group's allocable power budget. Under the global constraint that the sum of the target power of each charging pile in the set of charging piles that can participate in the regulation is less than or equal to the group's allocable power budget, the engine calculates and outputs the target power allocation result of each charging pile in the group in combination with the request of the set of charging piles that can participate in the regulation. The smoothing adjustment and command issuance module receives the target power allocation result, applies smoothing constraints to the power change, generates a power issuance command, and drives the charging pile to perform power adjustment through the communication link, thereby completing the dynamic power scheduling of the charging pile oriented towards the transformer group capacity constraint.

2. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The step of the power budget calculation module in calculating the group-assignable power budget at the current moment further includes: Determine the smaller of the total physical capacity of the transformer and the converted rated operating power of the transformer, and define the smaller value as the benchmark safety threshold power. For each charging pile in the set of charging piles with communication abnormalities, its current power occupancy value is forcibly set to the preset conservative power limit. The conservative power limit value is set to one of the following: the rated power value on the device nameplate, the historical peak power, the upper limit of the historical quantile, or the upper limit of the estimated value for the most recent N periods. Calculate the difference between the baseline safety threshold power and the uncontrolled load power, and subtract the conservative allowance power of all the charging piles with communication abnormalities. The difference is corrected by non-negative constraint logic to obtain the group's allocatable power budget.

3. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The steps of the data acquisition and status management module in generating a set of charging piles with communication anomalies and obtaining the power of uncontrolled loads include: The communication connection status of each charging pile in the group is monitored in real time. When it is determined that the target charging pile has failed to receive a communication heartbeat for N consecutive times or the data packet loss rate within a preset time window of T seconds exceeds a set threshold, the target charging pile is marked as the communication abnormal charging pile and added to the communication abnormal charging pile set. The uncontrolled load power is obtained and calculated by either subtracting the real-time power values ​​of all online controlled charging piles from the total meter power value, or by reading the data from independent metering instruments connected to the uncontrolled load circuit.

4. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The steps for the strategy engine and allocation module to calculate and output the target power allocation results for each charging pile in the group include: Obtain the vehicle demand power and corresponding comprehensive weighting coefficient of each charging pile in the set of charging piles that can participate in regulation; Determine whether the sum of the vehicle power demand of all the charging piles is greater than the group's allocable power budget; When the judgment result is yes, the congestion control logic is activated, and the group's allocable power budget is allocated according to the proportion of the product of the vehicle demand power and the comprehensive weighting coefficient of each charging pile to the total weighted demand, and the preliminary target power allocation result is calculated. The preliminary target power allocation result is subjected to device-level physical constraint verification to ensure that the final target power allocation result is between the minimum physical operating power of the charging pile and the power required by the vehicle, and does not exceed the maximum physical output power of the charging pile.

5. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 4, characterized in that, The comprehensive weighting coefficient is determined through a battery state response strategy, and the steps include: Obtain real-time battery state of charge data for each of the vehicles connected to the charging piles; When the vehicle's battery state of charge is lower than a preset low charge threshold, a higher weighting adjustment coefficient is assigned to the charging pile. When the vehicle's battery state of charge is between the low charge threshold and the high charge threshold, an intermediate weight coefficient is assigned to the charging pile or a weight coefficient is determined according to a preset mapping function. When the vehicle's battery state of charge is higher than a preset high charge threshold, a lower weighting adjustment coefficient is assigned to the charging pile.

6. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 4, characterized in that, The method also includes processing steps for extremely congested scenarios: When the calculated target power allocation result for a single charging pile is lower than the minimum physical operating power of the charging pile, a low power cutoff logic is executed to forcibly correct the target power allocation result for a single charging pile to zero, and the released power quota is recovered into the group's allocable power budget for redistribution to the charging piles that have not been cut off, until there are no allocable objects or the group's allocable power budget is exhausted. It also automatically switches to a polling mode, dividing the time axis into several time slices of fixed length. Within each time slice, only a portion of the charging piles are selected for their allowed output power, and the selected charging piles are rotated between adjacent time slices.

7. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The steps of generating and issuing power commands by the smooth adjustment and command issuance module include: Read the power command actually issued to each of the charging piles in the previous scheduling cycle; Calculate the maximum allowable step size based on the preset power ramp rate limit and the scheduling cycle length; Using the actual power command issued in the previous scheduling cycle as the reference center and the maximum allowable change step size as the radius, the safe power allowable range at the current moment is constructed. The target power allocation result output by the strategy engine and the allocation module is forcibly constrained within the safe power allowable range. The final power command is obtained by taking the smaller value between the target power allocation result and the upper limit of the range, and then taking the larger value between the smaller value and the lower limit of the range.

8. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The method also includes a closed-loop instruction issuance step: After the power command is issued, the data acquisition and status management module reads the actual output power of the charging pile and calculates the power tracking deviation between the actual output power and the issued power command. When the power tracking deviation continues to exceed the allowable steady-state deviation threshold and the duration exceeds the response delay tolerance time, the charging pile is determined to be in a command out-of-sync state. The charging pile that is out of step with the command is marked as the communication abnormal charging pile and is identified as controlled failure. In the calculation process of the next scheduling cycle, the charging pile that is out of step with the command is removed from the set of charging piles that can participate in the regulation and instead performs conservative quota power deduction.

9. The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints according to claim 1, characterized in that, The method employs a dual-mode driving mechanism for triggering: The data acquisition and status management module is equipped with a system timer. When the time count value reaches the global scheduling cycle, a periodic clock trigger signal is generated to start the scheduling process. The data acquisition and status management module scans the connection confirmation signal and fault alarm signal of the charging pile in the group in real time. When it detects topology or status change events including charging pile online or offline, equipment fault alarm, and transformer capacity threshold change, it forcibly generates an asynchronous event trigger signal to start the scheduling process. When the system receives a trigger signal, it freezes all real-time data at the current moment to generate a unique input state vector, which is then used by the power budget calculation module, the strategy engine, and the allocation module for calculation.

10. A dynamic power dispatching system for charging piles oriented towards transformer capacity constraints, characterized in that, The dynamic power scheduling method for charging piles oriented towards transformer capacity constraints, as described in any one of claims 1-9, includes: The group parameter database is used to store group-level constraint parameters, a list of charging piles within the group, weight parameters of each charging pile, and power quota parameters of abnormal charging piles. The data acquisition and status management module is used to acquire real-time physical parameters of the transformer group and real-time operating data of each charging pile in the group, maintain the communication connection status of the charging piles and generate a set of charging piles that can participate in regulation, acquire uncontrolled load power, and is responsible for generating trigger signals and freezing input status vectors based on a dual-mode drive mechanism of periodic clock signals and asynchronous topology event signals. The power budget calculation module is used to calculate the group-allocable power budget at the current moment by deducting the power of the uncontrolled load and the conservative allowance power of the charging pile with communication failure, under the constraints of the total physical capacity of the transformer and the group-level safety threshold. The strategy engine and allocation module are used to calculate and output the target power allocation result under the constraints of the group of allocable power budgets, combined with the vehicle demand power and weight parameters of each charging pile. The smoothing adjustment and command issuance module is used to receive the target power allocation result, smooth the power change based on the preset power ramp rate limit, generate the final power issuance command and send it to the charging pile, and is also responsible for monitoring power tracking deviation, identifying command out-of-sync state and executing closed-loop feedback logic.

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