A charging pile group dynamic power distribution method and system based on load prediction

Abstract

A dynamic power allocation method and system for charging pile clusters based on load forecasting, relating to the field of digital data processing, is disclosed. The method includes: real-time acquisition of charging data from charging piles; when a new vehicle requests charging, calculating the difference between its required power and the currently available power to obtain a power gap; if a power gap exists, calculating the amount of power reduction for each charging vehicle based on charging curve parameters and preset rules; calculating the charging time extension after the power reduction for each vehicle, and calculating the pile occupancy time sensitivity based on the originally estimated completion time; forming a power recovery candidate queue by sorting the sensitivity from lowest to highest; selecting suitable vehicles from the candidate queue to form a recovery scheme; calculating the total system pile occupancy time corresponding to the scheme; and selecting the scheme with the shortest total time as the optimal scheme; reducing the charging power of the selected vehicles according to the optimal scheme, and allocating the recovered power to new vehicles. Implementing this method can improve the utilization rate of charging piles.

Description

Technical Field

[0001] This application relates to the field of electrical digital data processing, and in particular to a method and system for dynamic power allocation of charging pile groups based on load forecasting. Background Technology

[0002] With the rapid growth in the number of new energy vehicles, charging stations have become the core locations for recharging electric vehicles. During peak charging periods, charging stations often face the contradiction of limited power capacity and strong charging demand. How to improve the overall operational efficiency of charging stations under limited power resources has become an important issue.

[0003] In related technologies, charging stations typically employ a fixed power allocation strategy to manage the power of charging piles. When a new vehicle arrives at a charging station and requests charging, the system checks whether the currently available power meets the demand. If the available power is insufficient, the vehicle is refused access or added to the waiting queue. Some charging stations use an equal distribution of available power, distributing the remaining power capacity evenly among all vehicles, ensuring that the charging power of each vehicle remains essentially constant during the charging process.

[0004] However, the aforementioned fixed power allocation strategy leads to low charging station turnover efficiency when the charging station capacity is saturated. When available power is insufficient, even if some vehicles that are charging are in the later stages of charging and have low sensitivity to power demand, the system cannot dynamically allocate the charging power of these vehicles to make room for new vehicles. This results in new vehicles waiting for a long time, while some vehicles on the charging stations only need lower power to complete charging. This uneven resource allocation reduces the utilization rate of charging station charging stations. Summary of the Invention

[0005] This application provides a dynamic power allocation method and system for charging pile groups based on load prediction, which can improve the utilization rate of charging pile positions by dynamically adjusting the power of vehicles being charged when the charging station capacity is limited.

[0006] Firstly, this application provides a dynamic power allocation method for charging pile groups based on load forecasting, applied to a dynamic power allocation system. The method includes: acquiring real-time charging data for all charging piles within a charging station, the real-time charging data including the current state of charge, current charging power, remaining charging current, and charging curve parameters for each vehicle corresponding to each charging pile; responding to a charging request from a new vehicle arriving at the charging station, acquiring the new vehicle's required charging power, calculating the difference between the current available power and the required charging power at the charging station to obtain a power gap; if the power gap is greater than zero, calculating the power adjustment amount that can be reduced for each vehicle currently charging according to a preset power adjustment rule based on the charging curve parameters and real-time charging data; and calculating the power reduction... After adjusting the charging rate, the charging time extension for each vehicle currently charging is calculated. This extension is then compared to the estimated charging completion time before the power reduction, yielding the charging station occupancy time sensitivity for each vehicle. All vehicles are sorted by their charging station occupancy time sensitivity from lowest to highest, creating a power recovery candidate queue. Vehicles are selected from this queue to form a power recovery scheme. The total system charging station occupancy time for each scheme is calculated, and the scheme that minimizes this total occupancy time is chosen as the optimal scheme. The charging power of the selected vehicles is reduced according to the optimal scheme, and the recovered power is allocated to new vehicles, ensuring that the recovered power is no greater than the reduction in charging power for the selected vehicles.

[0007] In the above embodiment, after acquiring real-time charging data from all charging piles within the charging station, the system can accurately identify the power gap when a new vehicle arrives. Based on the charging curve parameters, the system calculates the amount of power adjustment that can be reduced for each vehicle currently charging. Combining this with the charging time extension, it obtains the pile occupancy time sensitivity, prioritizing vehicles with low sensitivity in the power recovery candidate queue. From the candidate queue, the system selects the power recovery scheme that minimizes the total pile occupancy time, recovering some of the redundant charging power from other vehicles and allocating it to new vehicles. This allows new vehicles to connect to charging without waiting, while minimizing the charging time extension for vehicles with reduced power. This improves pile utilization and overall operational efficiency when charging station capacity is limited.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the charging time extension for each vehicle being charged after reducing the power adjustment amount, and calculating the charging time extension with the estimated charging completion time before the power reduction to obtain the charging station occupancy time sensitivity for each vehicle, specifically includes: dividing the interval between the current state of charge and the target state of charge into multiple charging stages according to the charging curve parameters, and obtaining the upper limit value of the charging power corresponding to each charging stage; calculating the adjusted charging power for each vehicle being charged, obtaining a temperature correction coefficient according to the current ambient temperature, and multiplying the adjusted charging power by the temperature correction coefficient to obtain the temperature-corrected charging power; calculating the minimum value between the temperature-corrected charging power and the upper limit value of the charging power in each charging stage as the actual charging power for the charging stage, and calculating the actual charging power based on the actual charging... The charging time for each charging stage is calculated based on the power and electricity demand corresponding to the charging stage. The charging times of all charging stages are summed to obtain the adjusted total charging time. The estimated charging completion time before the power reduction is obtained, and the adjusted total charging time is subtracted from the estimated charging completion time to obtain the basic charging time extension. User attribute information and battery status information of the vehicle currently charging are obtained. The user priority coefficient is calculated based on the user attribute information, and the battery health sensitivity coefficient is calculated based on the battery status information. The historical power adjustment records of the vehicle currently charging are queried, and the cumulative number of adjustments within the preset time window is counted. The fairness penalty coefficient is calculated based on the cumulative number of adjustments. The basic charging time extension, user priority coefficient, battery health sensitivity coefficient, and fairness penalty coefficient are weighted and summed to obtain the vehicle's charging station occupancy time sensitivity.

[0009] In the above embodiment, the system divides the charging interval into multiple charging stages. In each stage, the minimum value between the temperature-corrected charging power and the upper limit of the power is calculated as the actual charging power. The charging time of each stage is summed to obtain the adjusted total charging time. A user priority coefficient is calculated based on user attribute information, a battery health sensitivity coefficient is calculated based on battery status information, and a fairness penalty coefficient is obtained by statistically analyzing historical power adjustment records. The weighted sum of the basic charging time extension and the three coefficients yields the charging station occupancy time sensitivity. This multi-dimensional comprehensive evaluation method ensures that power adjustments prioritize vehicles with minimal impact on charging completion time, low user priority, minimal impact on battery health, and fewer historical adjustment occurrences, thus balancing charging efficiency, user experience, battery protection, and scheduling fairness.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the steps of selecting vehicles from the power recovery candidate queue to form a power recovery scheme, calculating the total system charging pile occupancy time corresponding to the power recovery scheme, and selecting the power recovery scheme that minimizes the total system charging pile occupancy time as the optimal power recovery scheme specifically include: selecting vehicles sequentially starting from the head of the power recovery candidate queue, accumulating the power adjustment amount corresponding to the selected vehicles, and accumulating the charging time extension amount corresponding to the selected vehicles; when the accumulated value of the power adjustment amount first reaches or exceeds the power gap, recording the number of currently selected vehicles and the accumulated value of the charging time extension amount; continuing to select vehicles, calculating the power adjustment amount and charging time extension amount corresponding to the newly selected vehicles, dividing the power adjustment amount and the charging time extension amount to obtain the power efficiency ratio; when the power efficiency ratio is less than a preset efficiency ratio, the following steps are taken: When the rate threshold is reached, the selection stops, resulting in a pre-screened vehicle set. Vehicle combinations that meet the power deficit are enumerated within this set. The adjusted total charging time of the selected vehicles in each combination is accumulated, as are the original estimated charging completion times of the unselected vehicles. The two accumulated values ​​are summed to obtain the total system charging station occupancy time for the vehicle combination. The total system charging station occupancy time for all vehicle combinations is compared, and the vehicle combination with the minimum total system charging station occupancy time is selected as the preliminary optimal solution. Based on the historical load data of the charging station, the probability of new vehicles arriving within a preset time period is calculated. When the probability value is greater than a preset probability threshold, the total recovered power in the preliminary optimal solution is multiplied by a preset redundancy coefficient to obtain the adjusted target recovered power. Based on the adjusted target recovered power, vehicle combinations are reselected from the pre-screened vehicle set to obtain the optimal power recovery solution.

[0011] In the above embodiment, the system sequentially selects vehicles from the head of the candidate queue and accumulates the power adjustment amount. When the accumulated value first meets the power gap, the number of vehicles is recorded. Vehicles are then selected again, and the power efficiency ratio is calculated. When the ratio is lower than the efficiency threshold, the system stops obtaining a pre-screened vehicle set. Vehicle combinations are enumerated in this set, and the total system pile occupancy time for each combination is calculated. The minimum value is selected as the initial optimal solution. The probability of future new vehicle arrivals is predicted based on historical load data. When the probability is high, the total recovered power is multiplied by a redundancy coefficient, and vehicle combinations are reselected. This two-stage optimization strategy avoids the computational complexity of global enumeration and, based on load prediction, reserves power redundancy, reducing the frequency of power adjustments when new vehicles arrive.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the step of reducing the charging power of selected vehicles according to the optimal power recovery scheme and allocating the recovered power to new vehicles specifically includes: obtaining the current charging power and corresponding power adjustment amount of each selected vehicle in the optimal power recovery scheme; subtracting the power adjustment amount from the current charging power to obtain the target charging power; dividing the difference between the current charging power and the target charging power into segments according to a preset exponential decay function to obtain multiple power adjustment stages and a staged power target value corresponding to each power adjustment stage; sending a power adjustment command corresponding to the current power adjustment stage to the selected vehicles; collecting the actual charging power and battery temperature change rate of the selected vehicles after waiting for a preset time; determining whether the actual charging power reaches the staged power target value and whether the battery temperature change rate is less than a preset temperature change threshold; when the actual charging power reaches the staged power target value... When the target power value is reached and the battery temperature change rate is less than the preset temperature change threshold, the next power adjustment stage continues. When the actual charging power fails to reach the stage power target value or the battery temperature change rate is greater than or equal to the preset temperature change threshold, the next-ranked vehicle is selected from the power recovery candidate queue as a replacement vehicle. The power adjustment amounts corresponding to all vehicles that have completed power adjustment are accumulated to obtain the total actual recovered power. The total actual recovered power is multiplied by the preset initial allocation ratio to obtain the initial allocation power, which is then allocated to the new vehicle. The current state of charge of the selected vehicle is obtained every preset evaluation cycle. When the current state of charge reaches the preset high state of charge threshold, the power adjustment amount occupied by the selected vehicle is released to obtain the released power. Other vehicles with reduced power are arranged in descending order of charging pile occupancy time sensitivity, and the released power is allocated to vehicles ranked higher than the preset ranking.

[0013] In the above embodiment, the system segments the difference between the current charging power and the target charging power according to an exponential decay function to obtain multiple power adjustment stages and staged power target values, and sends power adjustment commands to the selected vehicles in stages. The system collects the actual charging power and battery temperature change rate to determine whether the stage target has been reached and the temperature change rate is below a threshold. If the target is not met, a replacement vehicle is selected from the candidate queue. The initial allocated power is obtained by multiplying the total actual recovered power by the initial allocation ratio and allocated to the new vehicle. The state of charge (SOC) of the selected vehicle is acquired every evaluation cycle. When the high SOC threshold is reached, the occupied power is released and allocated to other vehicles with reduced power in reverse order of sensitivity. This staged, gradual power adjustment avoids the impact of sudden charging power changes on the battery, and the dynamic release and redistribution mechanism improves the utilization efficiency of power resources.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, after reducing the charging power of the selected vehicle according to the optimal power recovery scheme and allocating the recovered power to the new vehicle, the method further includes: recording the start time and end time of power adjustment for each selected vehicle; subtracting the start time from the end time of power adjustment to obtain the actual adjustment time; comparing the actual adjustment time with a preset standard adjustment time; marking the selected vehicle as a vehicle with abnormal response when the actual adjustment time exceeds a preset multiple of the preset standard adjustment time; counting the cumulative number of times the vehicle with abnormal response is marked within a preset historical period; and removing the vehicle with abnormal response from the power recovery candidate queue when the cumulative number reaches a preset abnormal number threshold.

[0015] In the above embodiments, the system records the start and end times of power adjustment for each selected vehicle, calculates the actual adjustment time, and compares it with the standard adjustment time. When the actual time exceeds a preset multiple of the standard time, the vehicle is marked as having an abnormal response. The system counts the cumulative number of times the vehicle has been marked within the historical period, and when the cumulative number reaches the abnormal number threshold, the vehicle is removed from the power recovery candidate queue. This anomaly identification and removal mechanism can exclude vehicles whose power adjustment fails due to charging equipment failure, communication delay, or slow response of the battery management system, ensuring that all vehicles in the candidate queue have good power adjustment response capabilities, thus improving the reliability and success rate of the power recovery scheme.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after reducing the charging power of the selected vehicles according to the optimal power recovery scheme and allocating the recovered power to new vehicles, the method further includes: responding to charging requests issued simultaneously by multiple new vehicles, calculating the difference between the total power demand of the multiple new vehicles and the currently available power to obtain a total power gap; dividing the power recovery candidate queue into multiple sub-queues according to the recoverable power of a single vehicle, and combining the sub-queues according to the total power demand and the total power gap to obtain multiple candidate power recovery combinations; calculating the sum of the charging pile occupancy time sensitivity of the vehicles in each candidate power recovery combination, and selecting the combination with the smallest sum of sensitivity as the preferred combination; when a vehicle in the preferred combination experiences a charging interruption, calculating the alternative power deficit based on the power recovery amount of the interrupted vehicle, and selecting the vehicle with the lowest recoverable power that meets the alternative power deficit and the lowest charging pile occupancy time sensitivity from the remaining sub-queues as a substitute; classifying and labeling the vehicles in the power recovery candidate queue according to their charging status and recoverable power, and grouping vehicles with the same charging characteristics into the same scheduling level.

[0017] In the above embodiments, when the system responds to simultaneous charging requests from multiple new vehicles, it calculates the difference between the total demand power and the available power to obtain the total power gap. The candidate queue is then divided into multiple sub-queues based on the recoverable power of each vehicle and combined. For each candidate power recovery combination, the sum of vehicle sensitivities is calculated, and the minimum value is selected as the preferred combination. When charging is interrupted in a preferred combination, a candidate power gap is calculated based on the power recovery amount of the interrupted vehicle, and the vehicle with the lowest sensitivity that meets the gap requirement is selected from the remaining sub-queues as a substitute. Vehicles in the candidate queues are categorized and labeled according to their charging status and recoverable power, and vehicles with the same charging characteristics are grouped into the same scheduling level. The sub-queue grading and combination optimization strategy improves the scheduling efficiency when multiple vehicles request charging concurrently, and the substitute mechanism ensures the execution stability of the power recovery scheme.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after classifying and labeling vehicles in the power recovery candidate queue according to their charging status and recoverable power, and grouping vehicles with the same charging characteristics into the same scheduling level, the method further includes: obtaining the remaining charging demand time of vehicles in each scheduling level, dividing the scheduling level into a recent off-grid level and a long-term on-grid level according to the remaining charging demand time; when the recoverable power of vehicles in the long-term on-grid level is insufficient, calculating the ratio of recent off-grid time to power adjustment cycle, and selecting vehicles in the recent off-grid level with a ratio greater than a preset threshold to supplement power recovery.

[0019] In the above embodiments, the system obtains the remaining charging time of vehicles in each scheduling level and divides the scheduling levels into near-off-grid level and long-term on-grid level according to the remaining time. When the recoverable power of vehicles in the long-term on-grid level is insufficient, the ratio of near-off-grid time to power adjustment cycle is calculated, and vehicles in the near-off-grid level with a ratio greater than a preset threshold are selected to supplement power recovery. This cross-level dynamic scheduling mechanism expands the range of candidate vehicles for power recovery. For vehicles that are about to be disconnected and have a short remaining charging time, the ratio judgment ensures that they still have enough time to complete the charging task after power adjustment. This increases the total amount of recoverable power of the system without affecting the charging completion of vehicles that are near-off-grid, and improves the flexibility of power resource allocation.

[0020] In a second aspect, embodiments of this application provide a dynamic power allocation system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the dynamic power allocation system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a dynamic power allocation system, cause the dynamic power allocation system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a dynamic power allocation system, cause the dynamic power allocation system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the dynamic power distribution system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. This application, by acquiring real-time charging data from all charging piles within a charging station, can accurately identify the power gap when a new vehicle arrives. Based on charging curve parameters, it calculates the amount of power adjustment that can be reduced for each charging vehicle, and combines this with the charging time extension to obtain the pile occupancy time sensitivity. Vehicles with low sensitivity are prioritized for inclusion in the power recovery candidate queue. From the candidate queue, the power recovery scheme that minimizes the total pile occupancy time is selected, recovering some of the redundant charging power from other vehicles and allocating it to new vehicles. This allows new vehicles to connect to charging without waiting, while minimizing the charging time extension for vehicles with reduced power. This improves pile utilization and overall operational efficiency when charging station capacity is limited.

[0026] 2. This application divides the charging interval into multiple charging stages through the system. In each stage, the minimum value between the temperature-corrected charging power and the upper limit of the power is calculated as the actual charging power. The total adjusted charging time is obtained by summing the charging times of each stage. A user priority coefficient is calculated based on user attribute information, a battery health sensitivity coefficient is calculated based on battery status information, and a fairness penalty coefficient is obtained by statistically analyzing historical power adjustment records. The weighted sum of the basic charging time extension and the three coefficients yields the charging station occupancy time sensitivity. This multi-dimensional comprehensive evaluation method ensures that power adjustments prioritize vehicles with minimal impact on charging completion time, low user priority, minimal impact on battery health, and fewer historical adjustment occurrences, thus balancing charging efficiency, user experience, battery protection, and scheduling fairness.

[0027] 3. This application uses a system to sequentially select vehicles from the head of the candidate queue and accumulate power adjustment amounts. When the accumulated value first meets the power gap, the number of vehicles is recorded. Vehicle selection continues, and the power efficiency ratio is calculated. When the ratio falls below an efficiency threshold, the process stops, resulting in a pre-selected vehicle set. Vehicle combinations are enumerated within this set, and the total system pile occupancy time for each combination is calculated. The minimum value is selected as the initial optimal solution. The probability of future new vehicle arrivals is predicted based on historical load data. When the probability is high, the total recovered power is multiplied by a redundancy coefficient, and vehicle combinations are reselected. This two-stage optimization strategy avoids the computational complexity of global enumeration and, based on load prediction, reserves power redundancy, reducing the frequency of power adjustments when new vehicles arrive. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a dynamic power allocation method for charging pile groups based on load prediction in an embodiment of this application.

[0029] Figure 2 This is another flowchart illustrating the dynamic power allocation method for charging pile groups based on load prediction in the embodiments of this application;

[0030] Figure 3 This is a schematic diagram of the physical device structure of a dynamic power distribution system in the embodiments of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] To facilitate understanding, the application scenarios of the embodiments of this application are described below.

[0034] A charging station in a city's commercial district is equipped with 20 charging piles, with a total power capacity of 1000kW. During the evening rush hour on a weekday, 18 charging piles are already occupied, with a total charging power of 950kW. At this time, three new cars arrive simultaneously requesting charging, each requiring 60kW, for a total demand of 180kW, far exceeding the currently available 50kW. Traditionally, these three cars would have to wait, but some vehicles already at the station are charged to over 80%, requiring only 30kW to complete their charging. The key issue in improving the charging station's operational efficiency is how to allocate power to allow new cars to connect to the charging station as quickly as possible without affecting the charging completion time of vehicles already charging.

[0035] When using the existing fixed power allocation strategy, the system detected that the available power was only 50kW, which was insufficient to meet the 180kW demand of the three new vehicles, and directly added these three vehicles to the waiting queue. The 18 vehicles already charging at the station continued to charge at their current power, with five vehicles already at 85% charge still occupying 60kW each, even though the actual power required was only 35kW due to charging curve limitations. The system could not identify the power redundancy of these vehicles, nor could it dynamically reclaim excess power. The three new vehicles waited an average of 25 minutes before finally getting a charging station, during which time approximately 125kW of power resources within the station were wasted.

[0036] After adopting the proposed solution, the system acquires real-time charging data from 18 vehicles currently charging and calculates a power shortfall of 180kW. Based on charging curve parameters, the system identifies 8 vehicles whose power can be reduced, calculates the charging station occupancy time sensitivity of each vehicle, and generates a candidate queue. The 5 vehicles with the lowest sensitivity are selected from the queue, and their charging power is reduced from 60kW to 45kW, recovering 15kW from each vehicle, for a total recovery of 75kW. The system performs power adjustment in stages according to an exponential decay function, monitoring the battery temperature change rate to ensure safety. The recovered 75kW is allocated to two new vehicles, each receiving 30kW for initial charging, while the third vehicle receives released power after a 5-minute wait. Overall charging station occupancy time is reduced by 18%.

[0037] To facilitate understanding, the method provided in this implementation will be described in detail below, using the above scenario as an example. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a dynamic power allocation method for charging pile groups based on load prediction in an embodiment of this application.

[0038] S101. Obtain real-time charging data for all charging piles in the charging station. The real-time charging data includes the current state of charge, current charging power, remaining charging current, and charging curve parameters for each vehicle corresponding to each charging pile.

[0039] Among them, charging piles refer to fixed power supply equipment that provides charging services for electric vehicles; real-time charging data represents various parameter information in the current charging process; current state of charge refers to the percentage of the battery's current stored capacity relative to its rated capacity; current charging power represents the actual input power value during the charging process; remaining charging current refers to the amount of remaining current required to complete charging; and charging curve parameters are used to describe the characteristics of current, voltage, power, and other parameters changing over time during the charging process.

[0040] This step is continuously executed during the operation of the charging station to monitor the real-time working status of each charging pile. Specifically, the system acquires charging data through the communication interface with the charging piles, including collecting information such as the battery status and charging parameters of each vehicle currently charging. This data is then processed and stored uniformly to provide a data foundation for subsequent power allocation decisions.

[0041] In some embodiments, real-time charging data acquisition can be achieved through the following methods: The system first establishes a real-time communication connection with the charging pile and sends data request commands to the charging pile periodically using a preset data acquisition cycle; upon receiving the request, the charging pile returns the currently measured parameter values; the system verifies the validity of the returned data, removes outliers, and updates the database. Optionally, the charging pile can also actively report data periodically: The charging pile collects data at preset time intervals and encapsulates it into a standard format; the data packets are sent to the system server via a communication network; the system parses the data packets and updates the storage. It is understood that other data acquisition methods can also be used to acquire charging data, and this is not limited here.

[0042] S102. In response to a new vehicle's charging request upon arrival at the charging station, obtain the new vehicle's required charging power, calculate the difference between the charging station's current available power and the required charging power, and obtain the power gap.

[0043] Among them, "new vehicle" refers to an electric vehicle that has just arrived at the charging station and requested charging service; "demanded charging power" indicates the charging power value requested by the new vehicle; "currently available power" refers to the remaining amount after subtracting the used power from the total power capacity of the charging station; and "power gap" indicates the difference between the demanded power and the available power.

[0044] This step is triggered when a new vehicle arrives at the charging station and sends a charging request. Specifically, after receiving the charging request, the system first reads the new vehicle's charging demand information, then queries the current power usage of the charging station, and calculates whether there is a power shortage and the size of the shortage, providing a basis for subsequent power allocation.

[0045] In some embodiments, the power gap can be obtained as follows: the system obtains the battery parameters and charging requirements of the new vehicle through the on-board terminal, calculates the standard charging power in combination with the charging mode; queries the total power capacity and current power consumption of the charging station in real time, calculates the remaining available power; and subtracts the available power from the required power to obtain the power gap. Optionally, a preset power level method can also be used: the system pre-sets several standard charging power levels; selects an appropriate power level according to the charging requirements of the new vehicle; and calculates the difference between the selected level and the available power. It is understood that other methods can also be used to calculate the power gap, which are not limited here.

[0046] S103. If the power gap is greater than zero, calculate the amount of power adjustment that can be reduced for each vehicle being charged according to the preset power adjustment rules based on the charging curve parameters and real-time charging data.

[0047] Among them, the power adjustment rule refers to the standard and method used to calculate the adjustable power range of each charging pile; the power adjustment amount represents the power value that each charging pile can reduce; and the charging curve parameters are used to determine the power adjustment space at different charging stages.

[0048] This step is executed after a power deficit is confirmed. Specifically, the system calculates the amount of charging power that can be reduced for each vehicle based on pre-set power adjustment rules, combined with the charging curve characteristics and current charging status of each vehicle, providing a feasibility analysis basis for subsequent selection of power recovery schemes.

[0049] In some embodiments, the power adjustment amount can be calculated as follows: the system divides the charging process into constant current and constant voltage stages according to the charging curve; in the constant current stage, the power reduction is calculated according to a preset ratio; in the constant voltage stage, the actual required power is calculated based on the current voltage and current, and the difference between the current power and the calculated power is used as the adjustable amount. Optionally, it can also be calculated based on the charging state: the system sets the minimum charging power requirement corresponding to different states of charge; the difference between the current power and the minimum requirement is used as the adjustable amount; and corrections are made considering factors such as temperature. It is understood that other methods can also be used to calculate the power adjustment amount, which are not limited here.

[0050] S104. Calculate the extension of charging time for each vehicle after reducing the power adjustment amount. Calculate the extension of charging time with the estimated charging completion time before reducing the power to obtain the charging station occupancy time sensitivity for each vehicle.

[0051] Among them, the charging time extension represents the increase in charging time caused by reducing power; the estimated charging completion time refers to the estimated time when charging is completed while maintaining the current power; and the pile occupancy time sensitivity is used to measure the degree of impact of power adjustment on charging time.

[0052] This step is performed after calculating the adjustable power for each vehicle. Specifically, the system recalculates the time required to complete charging based on the adjusted charging power, compares it with the original estimated completion time to obtain the time extension, and combines it with other factors to calculate the charging station occupancy time sensitivity, which is used for subsequent vehicle priority ranking.

[0053] In some embodiments, sensitivity can be calculated as follows: the system calculates the charging time for each charging stage after power adjustment based on the charging curve; the total charging time is accumulated and subtracted from the original time; and the sensitivity is calculated by weighting factors such as user type and battery status. Optionally, a statistical model can also be used: a correspondence between power adjustment and time extension is established based on historical data; the current adjustment scenario is substituted into the model to calculate the extension time; and the sensitivity is obtained by comprehensively considering multiple influencing factors. It is understood that other methods can also be used to calculate time sensitivity, and this is not limited here.

[0054] In some embodiments, this step specifically includes:

[0055] Based on the charging curve parameters, the interval between the current state of charge and the target state of charge is divided into multiple charging stages. The upper limit of the charging power corresponding to each charging stage is obtained, and the adjusted charging power for each vehicle being charged is calculated. A temperature correction coefficient is obtained based on the current ambient temperature. The adjusted charging power is multiplied by the temperature correction coefficient to obtain the temperature-corrected charging power. Within each charging stage, the minimum value between the temperature-corrected charging power and the upper limit of the charging power is calculated as the actual charging power for that stage. The charging time for each charging stage is calculated based on the actual charging power and the corresponding energy demand. The charging times of all charging stages are summed to obtain the adjusted total charging power. The process involves: obtaining the estimated charging completion time before power reduction; subtracting the estimated charging completion time from the adjusted total charging time to obtain the basic charging time extension; obtaining user attribute information and battery status information of the vehicle currently charging; calculating the user priority coefficient based on the user attribute information and the battery health sensitivity coefficient based on the battery status information; querying the historical power adjustment records of the vehicle currently charging; counting the cumulative number of adjustments within a preset time window; calculating the fairness penalty coefficient based on the cumulative number of adjustments; and weighting and summing the basic charging time extension, user priority coefficient, battery health sensitivity coefficient, and fairness penalty coefficient to obtain the vehicle's charging station occupancy time sensitivity.

[0056] The calculation process for charging pile occupancy time sensitivity first involves dividing the range from the current state of charge (SOC) to the target SOC into multiple charging stages (e.g., 0-20%, 20-50%, 50-80%, 80-100%) based on battery characteristics, according to the charging curve parameters. The upper limit of charging power for each stage is then obtained. For each vehicle currently charging, the adjusted charging power is calculated, and the current ambient temperature is obtained by looking up the corresponding temperature correction coefficient. The adjusted charging power is multiplied by the temperature correction coefficient to obtain the temperature-corrected actual usable charging power. Within each charging stage, the temperature-corrected charging power is compared with the upper limit of charging power for that stage, and the minimum of the two is taken as the actual charging power for that stage. Based on the actual charging power and the energy demand for each stage (target SOC minus initial SOC multiplied by battery capacity), the charging time for each stage is calculated. The charging times for all stages are summed to obtain the adjusted total charging time. The estimated charging completion time before power reduction is obtained, and the adjusted total charging time is subtracted from the original estimated completion time to obtain the basic charging time extension. Then, user attribute information (such as membership level, historical credit, etc.) is obtained to calculate the user priority coefficient, battery status information (such as cycle count, health, etc.) is obtained to calculate the battery health sensitivity coefficient, and the power adjustment records of the vehicle within a preset time window (usually 24 hours) are queried and the cumulative number of adjustments is counted to calculate the fairness penalty coefficient. Finally, the basic charging time extension (weight w1), user priority coefficient (weight w2), battery health sensitivity coefficient (weight w3), and fairness penalty coefficient (weight w4) are weighted and summed, with the sum of each weight being 1, to obtain the vehicle's charging station occupancy time sensitivity. This value comprehensively reflects the degree of impact of power adjustment on the vehicle.

[0057] S105. Sort all charging vehicles according to the sensitivity of charging pile occupancy time from smallest to largest to obtain the power recovery candidate queue.

[0058] Among them, sorting refers to arranging the data in order of size according to specific indicators; the sensitivity of charging pile occupancy time represents a quantitative indicator of the impact of power adjustment on charging time; and the power recovery candidate queue refers to the sequence of vehicles that can be selected after being sorted by priority.

[0059] This step is performed after calculating the charging station occupancy time sensitivity of each vehicle. Specifically, the system sorts all vehicles currently charging according to their charging station occupancy time sensitivity from smallest to largest. The lower the sensitivity, the less impact power adjustment has on the charging time of the vehicle, and the higher the priority is given to power adjustment. The sorting results form a candidate queue for subsequent selection.

[0060] In some embodiments, sorting can be implemented as follows: the system first constructs a key-value pair data structure for vehicles and their sensitivities; sorts the sensitivities in ascending order using the quicksort algorithm; and stores the sorting results in a queue data structure. Optionally, a hierarchical sorting method can also be used: the sensitivities are divided into multiple level intervals; the vehicles within each interval are then sorted a second time; and a queue is constructed according to the interval priority and the second sorting results. It is understood that other methods can also be used to sort vehicles, and this is not limited here.

[0061] S106. Select a vehicle group from the power recovery candidate queue to form a power recovery scheme, calculate the total system pile occupancy time corresponding to the power recovery scheme, and select the power recovery scheme that minimizes the total system pile occupancy time as the optimal power recovery scheme.

[0062] Among them, the power recovery scheme refers to the combination of vehicles selected from the candidate queue for adjusting power; the total occupancy time of the charging piles represents the cumulative time required for all charging vehicles to complete charging; the optimal power recovery scheme refers to the scheme that minimizes the total occupancy time while meeting power demand.

[0063] This step is performed after the power recovery candidate queue is obtained. Specifically, the system selects different vehicle combinations from the candidate queue to form multiple alternative schemes, calculates the total system charging station occupancy time after implementing each scheme, and selects the scheme with the shortest total time as the optimal scheme by comparison, ensuring that the power demand is met while minimizing the impact on the overall charging efficiency.

[0064] In some embodiments, the optimal solution can be selected as follows: the system selects vehicles from the head of the queue and calculates the cumulative recoverable power; when the cumulative value meets the requirement, the current vehicle combination is recorded; multiple combinations that meet the conditions are obtained by continuing to select; the total occupancy time of each combination is calculated and compared. Optionally, a dynamic programming approach can also be used: power requirement is used as a constraint; total occupancy time is used as the optimization objective; and the optimal vehicle combination is solved using a dynamic programming algorithm. It is understood that other methods can also be used to select the optimal solution, which are not limited here.

[0065] In some embodiments, this step specifically includes:

[0066] Starting from the head of the power recovery candidate queue, vehicles are selected sequentially. The power adjustment amount and charging time extension amount corresponding to the selected vehicles are accumulated. When the accumulated value of the power adjustment amount first reaches or exceeds the power gap, the number of currently selected vehicles and the accumulated value of the charging time extension amount are recorded. Vehicles are selected again, and the power adjustment amount and charging time extension amount corresponding to the newly selected vehicles are calculated. The power efficiency ratio is obtained by dividing the power adjustment amount by the charging time extension amount. When the power efficiency ratio is less than a preset efficiency threshold, the selection stops, resulting in a pre-screened vehicle set. In the pre-screened vehicle set, combinations of vehicles that meet the power gap are enumerated, and the selected vehicles in each combination are... The total charging time of the selected vehicles is accumulated, and the original estimated charging completion time of the unselected vehicles is also accumulated. The two accumulated values ​​are added together to obtain the total system charging station occupancy time for the vehicle combination. The total system charging station occupancy time for all vehicle combinations is compared, and the vehicle combination with the minimum total system charging station occupancy time is selected as the preliminary optimal solution. The probability value of new vehicles arriving in the future within a preset time period is calculated based on the historical load data of the charging station. When the probability value is greater than the preset probability threshold, the total recoverable power in the preliminary optimal solution is multiplied by a preset redundancy coefficient to obtain the adjusted target recoverable power. Based on the adjusted target recoverable power, a new vehicle combination is selected from the pre-screened vehicle set to obtain the optimal power recovery solution.

[0067] The power recovery candidate queue refers to a sequence of vehicles selected based on their charging station occupancy time sensitivity, ordered from lowest to highest. Each vehicle has a specific adjustable power level and a corresponding charging time extension. The power adjustment amount represents the amount of charging power that each vehicle can reduce, measured in kilowatts (kW). The charging time extension refers to the increase in charging completion time due to the reduced charging power, measured in minutes. The power efficiency ratio, obtained by dividing the power adjustment amount by the time extension, measures the degree of time extension caused by a unit power adjustment. The pre-screened vehicle set is the group of candidate vehicles obtained after initial screening. The total system charging station occupancy time refers to the cumulative time required for all charging vehicles to complete the charging task. The preset redundancy coefficient is a constant greater than 1, used to reserve additional power capacity when calculating the target recovery power.

[0068] This step employs a multi-stage screening strategy to determine the optimal power recovery scheme. Starting from the head of the candidate queue, vehicles are selected one by one. The power adjustment amounts of the selected vehicles are accumulated to obtain the cumulative recoverable power, along with the corresponding charging time extension. When the cumulative recoverable power first reaches or exceeds the power deficit, the number of currently selected vehicles and the accumulated time extension are recorded. Vehicles are then selected, and the ratio of the power adjustment amount to the time extension for each newly selected vehicle is calculated—the power efficiency ratio. Selection stops when this ratio falls below a preset efficiency threshold, resulting in a pre-screened vehicle set. All vehicle combinations that meet the power deficit requirement are enumerated within this set. For each combination, the total charging time after adjustment for the selected vehicles and the sum of the original charging times for the unselected vehicles are calculated to obtain the total system charging station occupancy time for that combination. By comparing the total system charging station occupancy times of all combinations, the combination with the shortest total occupancy time is selected as the preliminary optimal scheme.

[0069] Based on historical load data of charging stations, time series analysis is used to calculate the probability of new vehicles arriving within a preset time period. When this probability value is greater than a preset probability threshold, it indicates that there may be new charging demand in the short term. At this time, the total recoverable power in the initial optimal solution is multiplied by a preset redundancy coefficient to obtain the adjusted target recoverable power. Finally, based on this new target recoverable power, a suitable combination of vehicles is reselected from the pre-screened vehicle set as the final optimal power recovery solution. For example, if there are 10 candidate vehicles with a power gap of 100kW, selecting 5 vehicles from the front of the queue can recover a total of 90kW. Continuing to select, the efficiency ratio of the 7th vehicle drops to 0.4kW / min, which is lower than the threshold of 0.5kW / min, resulting in a pre-screened set of 7 vehicles. In this set, a combinatorial optimization algorithm is used to select vehicles 3, 4, and 6, which can recover 102kW with the shortest total occupancy time. The probability of a new vehicle arriving within 30 minutes was calculated to be 0.85, which exceeds the threshold of 0.8. Multiplying 102kW by the redundancy factor of 1.2 yields the target recovery power of 122kW. Finally, vehicles 3, 4, 6, and 7 were selected to form the optimal solution.

[0070] S107. Reduce the charging power of the selected vehicle according to the optimal power recovery scheme, and allocate the recovered power to the new vehicle. The recovered power shall not be greater than the reduced charging power of the selected vehicle.

[0071] Among them, the selected vehicle refers to the vehicle in the optimal solution that is determined to require power adjustment; the recovered power represents the available power obtained after reducing the charging power of the selected vehicle; and the power allocation refers to the allocation of the recovered power to the new vehicle for use.

[0072] This step is executed after the optimal power recovery scheme is determined. Specifically, the system sends power adjustment commands to the selected vehicles according to the optimal scheme. After confirming that the power adjustment is successful, the recovered power is allocated to newly arriving vehicles, while ensuring that the power allocated to new vehicles does not exceed the actual amount of recovered power, thus guaranteeing the safe and stable operation of the system.

[0073] In some embodiments, power adjustment can be performed as follows: the system first sends a power reduction command to the selected vehicle; monitors the vehicle's response and actual power changes; and after confirming successful power adjustment, allocates power to new vehicles in batches. Optionally, a gradual adjustment can also be used: the power adjustment amount is divided into multiple steps; the power of the selected vehicle is gradually reduced; and the recovered power is simultaneously and gradually allocated to new vehicles. It is understood that other methods can also be used to perform power adjustment, which are not limited here.

[0074] In some embodiments, this step specifically includes:

[0075] The system obtains the current charging power and corresponding power adjustment amount for each selected vehicle in the optimal power recovery scheme. The target charging power is obtained by subtracting the power adjustment amount from the current charging power. The difference between the current charging power and the target charging power is segmented according to a preset exponential decay function to obtain multiple power adjustment stages and a staged power target value for each stage. A power adjustment command corresponding to the current power adjustment stage is sent to the selected vehicle. After waiting for a preset time, the actual charging power and battery temperature change rate of the selected vehicle are collected. It is determined whether the actual charging power reaches the staged power target value and whether the battery temperature change rate is less than a preset temperature change threshold. If the actual charging power reaches the staged power target value and the battery temperature change rate is less than the preset temperature change threshold, the next power adjustment stage is executed. During the rate adjustment phase, when the actual charging power fails to reach the phased power target value or the battery temperature change rate is greater than or equal to the preset temperature change threshold, the next-ranked vehicle is selected from the power recovery candidate queue as a replacement vehicle. The power adjustment amounts corresponding to all vehicles that have completed power adjustment are accumulated to obtain the total actual recovered power. The total actual recovered power is multiplied by the preset initial allocation ratio to obtain the initial allocation power. The initial allocation power is allocated to the new vehicle. The current state of charge of the selected vehicle is obtained every preset evaluation cycle. When the current state of charge reaches the preset high state of charge threshold, the power adjustment amount occupied by the selected vehicle is released to obtain the released power. Other vehicles with reduced power are arranged in descending order of charging pile occupancy time sensitivity, and the released power is allocated to vehicles whose ranking is higher than the preset ranking.

[0076] The optimal power recovery scheme refers to the best combination of vehicle power adjustments selected through an optimization algorithm, including the current charging power of each selected vehicle and the amount of power adjustment required. The target charging power represents the final power value the vehicle needs to reduce to, obtained by subtracting the power adjustment amount from the current charging power. A preset exponential decay function is used to divide the power adjustment process into multiple progressive stages, ensuring smooth power adjustment. The staged power target value refers to the intermediate power value to be achieved in each adjustment stage. The battery temperature change rate reflects the rate of temperature change of the battery during the power adjustment process and is used to monitor charging safety. The actual total recovered power refers to the sum of the actual power reductions of all vehicles that successfully completed power adjustments.

[0077] This step achieves safe adjustment of vehicle charging power through phased control. First, the current charging power and planned adjustment amount for each selected vehicle are acquired, and the final target charging power is calculated. An exponential decay function f(x) = P0 * e^(-λx) is used to divide the adjustment range from the current power to the target power into multiple phases, where P0 is the initial power difference, λ is the decay coefficient, and x is the time parameter. Each phase corresponds to a target power value. The system sends power adjustment commands to the vehicles in phase order, and after a preset time (e.g., 5 seconds), collects actual charging power and battery temperature change data. It determines whether the actual power reaches the target value of the current phase and whether the temperature change rate is within a safe range. If the conditions are met, the system proceeds to the next adjustment phase; otherwise, it selects the next vehicle from the candidate queue. The actual adjusted power of all adjusted vehicles is summed to obtain the total recovered power, which is then multiplied by a preset initial allocation ratio (e.g., 0.8) to calculate the power value that can be allocated to new vehicles.

[0078] The system checks the state of charge (SOC) of selected vehicles at fixed evaluation intervals (e.g., every 5 minutes). When a vehicle reaches a preset high SOC threshold (e.g., 85%), the power adjustment amount occupied by that vehicle is released. Other vehicles with reduced power are sorted in descending order of charging station occupancy time sensitivity, and the released power is preferentially allocated to the vehicles ranked higher. For example, if a vehicle's current charging power is 50kW and needs to be reduced by 20kW to 30kW, the adjustment process is divided into four stages using an exponential decay function: 45kW, 40kW, 35kW, and 30kW. At each stage, the actual power and temperature change rate (e.g., 0.5°C / min) are monitored. If the temperature change rate at a certain stage exceeds the threshold of 1°C / min, the next vehicle is selected from the candidate queue to replace it. Ultimately, a total of 18kW of power is actually recovered. 14.4kW is allocated to the new vehicle according to an initial allocation ratio of 0.8. The remaining power is released when the vehicle's SOC reaches 90%.

[0079] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2This is another flowchart illustrating the dynamic power allocation method for charging pile groups based on load prediction in the embodiments of this application.

[0080] S201. Reduce the charging power of the selected vehicle according to the optimal power recovery scheme, and allocate the recovered power to the new vehicle. The recovered power shall not be greater than the reduced charging power of the selected vehicle.

[0081] The optimal power recovery scheme refers to the calculated best combination of vehicles for power adjustment, including a list of vehicles requiring adjustment and the adjusted power value for each vehicle. Selected vehicles are those in the scheme whose charging power needs to be reduced. Recovered power represents the actual usable power value obtained after reducing the charging power from the selected vehicles.

[0082] In this step, the first step is to obtain a list of vehicles in the optimal solution and their corresponding target power adjustment values. For each selected vehicle, a power adjustment command is sent through the charging pile control interface to gradually reduce the charging power from the current value to the target value. To avoid sudden power fluctuations impacting the vehicle charging system, a segmented adjustment method is adopted: the range between the current power and the target power is divided into several equal parts, and an adjustment step is taken at a time, with the adjustment proceeding only after stabilization. After each vehicle completes its power adjustment, the actual power reduction is recorded and accumulated to obtain the total recovered power. The recovered power is then allocated to new vehicles, specifically according to their power requirements from smallest to largest. The power received by each new vehicle does not exceed its requested power value, and the total power allocated does not exceed the total amount of power actually recovered.

[0083] S202. Record the start and end times of power adjustment for each selected vehicle, and subtract the start time from the end time of power adjustment to obtain the actual adjustment time.

[0084] The power adjustment start time refers to the moment when the selected vehicle sends the first power adjustment command. The power adjustment end time refers to the moment when the vehicle's charging power reaches the target value and remains stable. The actual adjustment time represents the time consumed to complete the entire power adjustment process.

[0085] This step tracks the power adjustment process by recording timestamps. When power adjustment begins, the current system time is acquired and stored as the start time. During power adjustment, the actual charging power of the vehicle is continuously monitored. When the power value reaches the set target value and remains stable for multiple consecutive sampling periods, the current time is acquired as the end time. The timestamp of the start time is subtracted from the timestamp of the end time to obtain the actual adjustment time in milliseconds. The same time recording process is performed for each selected vehicle, and the vehicle number is associated with the corresponding adjustment time and stored for subsequent response time analysis.

[0086] S203. Compare the actual adjustment time with the preset standard adjustment time. When the actual adjustment time exceeds the preset multiple of the preset standard adjustment time, mark the selected vehicle as a vehicle with abnormal response.

[0087] The preset standard adjustment time refers to the baseline time that should be consumed to complete power adjustment under normal circumstances. The preset multiplier is used to set the acceptable time deviation range. Vehicles with abnormal response refer to those whose power adjustment time significantly exceeds the normal range.

[0088] This step analyzes the power adjustment response of each selected vehicle. First, the actual adjustment time is read from the storage and compared with a pre-set standard adjustment time. The standard adjustment time is determined based on the magnitude of the power adjustment; the larger the adjustment, the longer the allowed adjustment time. The specific calculation uses a piecewise function: when the adjustment is less than 5kW, the standard time is 2 seconds; when the adjustment is between 5-10kW, the standard time is 3 seconds; and when the adjustment is greater than 10kW, the standard time is 5 seconds. The actual time is divided by the standard time to obtain a multiplier. If this multiplier exceeds a preset threshold (usually set to 3), the vehicle is marked as having an abnormal response, and its status flag is updated in the database.

[0089] S204. Count the cumulative number of times that vehicles with abnormal response are marked within a preset historical period. When the cumulative number reaches the preset abnormal number threshold, remove the vehicles with abnormal response from the power recovery candidate queue.

[0090] The preset historical period refers to the time range for backtracking statistics, typically set to 24 hours. The cumulative count represents the total number of times a vehicle is marked as having an abnormal response within that period. The preset anomaly count threshold is used to determine whether to remove a vehicle from the candidate queue.

[0091] This step involves statistical analysis and processing of vehicles with abnormal responses. For newly marked vehicles with abnormal responses, their abnormal records within a preset historical period are queried. Specifically, the query method involves retrieving all records within that period from the abnormal record data table by vehicle ID and counting the number of records to obtain the cumulative count. The cumulative count is compared with a preset abnormal count threshold (usually set to 3). When the cumulative count reaches or exceeds the threshold, it indicates that the vehicle has frequently experienced abnormal responses. At this point, the vehicle ID is removed from the power recovery candidate queue, and a record for the vehicle is added to the blacklist table, containing information such as vehicle ID, removal time, and number of abnormal responses.

[0092] S205. In response to charging requests from multiple new vehicles simultaneously, calculate the difference between the total power demand of the multiple new vehicles and the current available power to obtain the total power gap.

[0093] Total power demand refers to the sum of charging power requests from multiple new vehicles. Currently available power refers to the remaining unallocated power capacity of the charging station. Total power deficit represents the additional power required to meet the charging needs of all new vehicles.

[0094] This step handles the scenario where multiple new vehicles request charging simultaneously. First, it receives all charging requests from the new vehicles, extracts the power demand value for each vehicle from the requests, and sums them up to obtain the total power demand. It then queries the charging station's power usage in real time, subtracting the allocated power from the total power capacity to obtain the current available power. Finally, it subtracts the available power from the sum of the demanded power to obtain the total power gap that needs to be filled through power recovery. If three new vehicles arrive simultaneously, each demanding 60kW, and the current available power is 50kW, then the total power gap is (60 × 3 - 50) = 130kW.

[0095] S206. Divide the candidate queue for power recovery into multiple sub-queues according to the amount of recoverable power per vehicle. Combine the sub-queues according to the total power demand and the total power gap to obtain multiple candidate power recovery combinations.

[0096] Single-vehicle recyclable power refers to the maximum power reduction that each candidate vehicle can achieve. A sub-queue is a sequence of vehicles with similar recyclable power. A candidate power recovery combination represents a vehicle combination scheme that can meet the power requirements.

[0097] This step constructs feasible power recovery schemes by grouping and combining candidate queues. First, the recoverable power of each vehicle in the candidate queues is read, and vehicles are assigned to different sub-queues according to their power value range: for example, 0-5kW for low-power queues, 5-10kW for medium-power queues, and above 10kW for high-power queues. Then, based on the total power deficit, different combinations of sub-queues are selected. For example, when the deficit is 130kW, a combination of 2 high-power queues (15kW each) and 8 medium-power queues (7.5kW each), or a combination of 3 high-power queues and 6 medium-power queues, etc., can be selected. All feasible combinations are recorded as candidate schemes.

[0098] S207. For each candidate power recovery combination, calculate the sum of the vehicle's pile position occupancy time sensitivity and select the combination with the smallest sum of sensitivity as the preferred combination.

[0099] Charging station occupancy time sensitivity refers to the quantitative indicator of the impact of power adjustment on charging time. The sum of sensitivities represents the cumulative sensitivity value of all vehicles in the combination scheme. The optimal combination refers to the vehicle combination that minimizes the impact on charging time while meeting power requirements.

[0100] This step selects the optimal power recovery scheme through calculation and comparison. For each vehicle in the candidate combination, its charging station occupancy time sensitivity value is extracted and accumulated. The accumulation process uses a weighted summation method, with the weight coefficient determined according to the vehicle's power adjustment amount: 1.0 for adjustment amounts in the 0-5kW range, 1.2 for the 5-10kW range, and 1.5 for adjustments above 10kW. The weighted sensitivity values ​​are then summed to obtain the total sensitivity of the combination. This calculation process is repeated for all candidate combinations to obtain the total sensitivity value for each combination. These total sensitivity values ​​are sorted from smallest to largest, and the combination with the lowest sensitivity is selected as the preferred combination. This selection method ensures that power demand is met while minimizing the impact on vehicle charging time.

[0101] S208. When a vehicle in the preferred combination experiences a charging interruption, calculate the alternative power deficit based on the power recovery amount of the interrupted vehicle, and select the vehicle with the least sensitivity to charging station occupancy time from the remaining sub-queues to replace it.

[0102] Power recovery refers to the power that the interrupted vehicle was originally planned to provide. Alternate power deficit indicates the amount of power that needs to be supplemented by a replacement vehicle. A replacement vehicle is a vehicle selected from the remaining candidate vehicles to replace the interrupted vehicle.

[0103] This step handles charging interruptions in the preferred charging combination. When a vehicle in the combination is detected to have stopped charging, its original planned power recovery amount is immediately recorded as a backup power deficit. Vehicles with recoverable power greater than or equal to the deficit are searched in the remaining sub-queues and sorted by their sensitivity to charging station occupancy time. A replacement is attempted starting with the vehicle with the lowest sensitivity: first, a test command is sent to verify the vehicle's response; if the response is normal, the vehicle is included in the combination scheme, replacing the interrupted vehicle; if the response is abnormal, the next candidate vehicle is tried. The replacement process must be completed within a preset time limit (usually 10 seconds) to ensure the timeliness of the power adjustment scheme.

[0104] S209. Classify and label the vehicles in the power recovery candidate queue according to their charging status and recoverable power, and group vehicles with the same charging characteristics into the same scheduling level.

[0105] Charging status includes information such as current charge level and charging stage. Charging characteristics refer to the common features exhibited by vehicles during the charging process. Scheduling levels are used to group vehicles with similar characteristics for management.

[0106] This step involves classifying and managing vehicles in the candidate queue. First, the charging status information for each vehicle is obtained, including the current percentage of charge, charging stage (constant current / constant voltage), and charging power. Based on these status parameters and the amount of recyclable power, a classification standard is established: by charge level, vehicles are divided into three categories: high charge (>80%), medium charge (50%-80%), and low charge (<50%); by charging stage, vehicles are divided into constant current charging and constant voltage charging; and by recyclable power, vehicles are divided into three categories: high power (>10kW), medium power (5-10kW), and low power (<5kW). Vehicles with the same classification standard are grouped into the same scheduling level, and a unique identifier is assigned to each level.

[0107] S210. Obtain the remaining time for vehicle charging demand in each scheduling level, and divide the scheduling level into near-offline level and long-term online level according to the remaining time for charging demand.

[0108] The remaining charging time refers to the estimated time needed to complete the charging task. The "Recent Off-Grid Level" includes vehicles expected to complete charging in a short time. The "Long-Term On-Grid Level" includes vehicles expected to require a longer charging time.

[0109] This step involves segmenting vehicles across different scheduling levels by time dimension. First, the remaining charging time for all vehicles in each scheduling level is obtained. This is calculated by dividing the difference between the target charging amount and the current charging amount by the current charging power to obtain the estimated remaining charging time. The calculated remaining time is then compared to a preset time threshold (usually 30 minutes): vehicles with a time less than the threshold are classified as recently disconnected, while those with a time greater than the threshold are classified as long-term connected. The network type tag for each scheduling level is then updated in the database for subsequent classification and management.

[0110] S211. When the recyclable power of a vehicle in the long-term grid-connected category is insufficient, calculate the ratio of the recent off-grid time to the power adjustment cycle, and select vehicles in the recent off-grid category with a ratio greater than a preset threshold to supplement the power recovery.

[0111] The power adjustment cycle refers to the time required to perform one complete power adjustment. The ratio of recent off-grid time to the power adjustment cycle indicates the number of adjustments a vehicle can perform before leaving the grid. A preset threshold is used to determine whether a vehicle is suitable for participating in power recovery.

[0112] This step expands the candidate pool when long-term on-grid vehicles cannot meet power requirements. First, the total recyclable power of long-term on-grid vehicles is calculated. If this is less than the required power, some recently off-grid vehicles are considered. For each recently off-grid vehicle, the ratio of its expected off-grid time to the standard power adjustment cycle (usually 1 minute) is calculated. If the ratio is greater than a preset threshold (usually 5), it indicates that the vehicle still has sufficient time to perform multiple power adjustments before completing charging, and this vehicle is added to the power recovery candidate list. The newly added vehicles are then inserted into appropriate positions according to the original sensitivity ranking rules.

[0113] The dynamic power distribution system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference]. Figure 3 This is a schematic diagram of the physical device structure of a dynamic power distribution system in an embodiment of this application.

[0114] It should be noted that, Figure 3 The structure of the dynamic power distribution system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0115] like Figure 3 As shown, the dynamic power distribution system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0116] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0117] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0118] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0120] Specifically, the dynamic power allocation system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the dynamic power allocation method for charging pile groups based on load prediction provided in the above embodiment.

[0121] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the dynamic power allocation system described in the above embodiments; or it may exist independently and not assembled into the dynamic power allocation system. The storage medium carries one or more computer programs that, when executed by a processor of the dynamic power allocation system, cause the dynamic power allocation system to implement the load prediction-based dynamic power allocation method for charging pile groups provided in the above embodiments.

[0122] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0123] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A load prediction-based charging pile group dynamic power distribution method, characterized in that, The method, applied to a dynamic power distribution system, includes: The system acquires real-time charging data for all charging piles within the charging station. The real-time charging data includes the current state of charge, current charging power, remaining charging current, and charging curve parameters for each vehicle corresponding to each charging pile. In response to a charging request from a new vehicle arriving at a charging station, the required charging power of the new vehicle is obtained, and the difference between the current available power of the charging station and the required charging power is calculated to obtain the power gap. If the power gap is greater than zero, the power adjustment amount that can be reduced for each vehicle being charged is calculated according to the charging curve parameters and the real-time charging data based on the preset power adjustment rules. Calculate the charging time extension for each of the vehicles being charged after reducing the power adjustment amount, and calculate the charging time extension with the estimated charging completion time before the power reduction to obtain the charging station occupancy time sensitivity for each vehicle. All vehicles currently charging are sorted in ascending order of their charging pile occupancy time sensitivity to obtain a power recovery candidate queue. Select a vehicle composition power recovery scheme from the power recovery candidate queue, calculate the total system pile occupancy time corresponding to the power recovery scheme, and select the power recovery scheme that minimizes the total system pile occupancy time as the optimal power recovery scheme. According to the optimal power recovery scheme, the charging power of the selected vehicle is reduced, and the recovered power is allocated to the new vehicle, wherein the recovered power is not greater than the reduced charging power of the selected vehicle.

2. The method of claim 1, wherein, The step of calculating the charging time extension for each vehicle being charged after reducing the power adjustment amount, and then calculating the charging time extension with the estimated charging completion time before the power reduction to obtain the charging station occupancy time sensitivity for each vehicle, specifically includes: Based on the charging curve parameters, the interval between the current state of charge and the target state of charge is divided into multiple charging stages, and the upper limit value of the charging power corresponding to each charging stage is obtained. Calculate the adjusted charging power for each of the vehicles currently being charged, obtain a temperature correction coefficient based on the current ambient temperature, and multiply the adjusted charging power by the temperature correction coefficient to obtain the temperature-corrected charging power. Within each charging stage, the minimum value between the temperature-corrected charging power and the upper limit of the charging power is calculated as the actual charging power of the charging stage. The charging time of each charging stage is calculated based on the actual charging power and the power demand corresponding to the charging stage. The charging times of all charging stages are summed to obtain the adjusted total charging time. Obtain the estimated charging completion time before reducing power, and subtract the estimated charging completion time from the adjusted total charging time to obtain the basic charging time extension. Obtain user attribute information and battery status information of the vehicle being charged; calculate user priority coefficient based on user attribute information; calculate battery health sensitivity coefficient based on battery status information; query historical power adjustment records of the vehicle being charged; count the cumulative number of adjustments within a preset time window; and calculate fairness penalty coefficient based on the cumulative number of adjustments. The vehicle's charging station occupancy time sensitivity is obtained by weighting and summing the basic charging time extension, the user priority coefficient, the battery health sensitivity coefficient, and the fairness penalty coefficient.

3. The method of claim 1, wherein, The steps of selecting vehicles to form a power recovery scheme from the power recovery candidate queue, calculating the total system pile occupancy time corresponding to the power recovery scheme, and selecting the power recovery scheme that minimizes the total system pile occupancy time as the optimal power recovery scheme specifically include: Starting from the head of the power recovery candidate queue, vehicles are selected sequentially. The power adjustment amount corresponding to the selected vehicles is accumulated, and the charging time extension amount corresponding to the selected vehicles is accumulated. When the accumulated value of the power adjustment amount first reaches or exceeds the power gap, the number of currently selected vehicles and the accumulated value of the charging time extension amount are recorded. Continue selecting vehicles and calculate the power adjustment amount and charging time extension amount corresponding to the newly selected vehicles. The power efficiency ratio is obtained by dividing the power adjustment amount by the charging time extension amount. When the power efficiency ratio is less than a preset efficiency threshold, the selection stops, and a pre-screened vehicle set is obtained. Enumerate the vehicle combinations that meet the power gap in the pre-screened vehicle set, accumulate the adjusted total charging time of the selected vehicles in each vehicle combination, accumulate the original estimated charging completion time of the unselected vehicles, and add the two accumulated values ​​to obtain the total system charging station occupancy time corresponding to the vehicle combination. Compare the total system pile occupancy time for all vehicle combinations, and select the vehicle combination with the minimum total system pile occupancy time as the preliminary optimal solution; The probability of a new vehicle arriving within a preset time period is calculated based on the historical load data of the charging station. When the probability value is greater than a preset probability threshold, the total recoverable power in the preliminary optimal scheme is multiplied by a preset redundancy coefficient to obtain the adjusted target recoverable power. Based on the adjusted target recoverable power, a new vehicle combination is selected from the pre-screened vehicle set to obtain the optimal power recovery scheme.

4. The method of claim 1, wherein, The step of reducing the charging power of the selected vehicle according to the optimal power recovery scheme and allocating the recovered power to the new vehicle specifically includes: The current charging power and the corresponding power adjustment amount of each selected vehicle in the optimal power recovery scheme are obtained, and the target charging power is obtained by subtracting the current charging power from the power adjustment amount. The difference between the current charging power and the target charging power is divided into segments according to a preset exponential decay function to obtain multiple power adjustment stages and a staged power target value corresponding to each power adjustment stage. Send the power adjustment command corresponding to the current power adjustment stage to the selected vehicle, and collect the actual charging power and battery temperature change rate of the selected vehicle after waiting for a preset time. Determine whether the actual charging power reaches the target power value for the specified stage and whether the battery temperature change rate is... If the actual charging power reaches the stage power target value and the battery temperature change rate is less than the preset temperature change threshold, the next power adjustment stage will continue to be executed. If the actual charging power does not reach the stage power target value or the battery temperature change rate is greater than or equal to the preset temperature change threshold, the next vehicle in the power recovery candidate queue will be selected as the replacement vehicle. The total actual recovered power is obtained by summing the power adjustment amounts corresponding to all vehicles that have completed power adjustment. The initial allocated power is obtained by multiplying the actual total recovered power by the preset initial allocation ratio, and the initial allocated power is allocated to the new vehicle. The current state of charge of the selected vehicle is obtained every preset evaluation cycle. When the current state of charge reaches a preset high state of charge threshold, the power adjustment amount occupied by the selected vehicle is released to obtain the released power. Other vehicles with reduced power are arranged in descending order of their sensitivity to the time of pile occupancy, and the released power is allocated to vehicles whose ranking is higher than the preset ranking.

5. The method of claim 1, wherein, After the step of reducing the charging power of the selected vehicle according to the optimal power recovery scheme and allocating the recovered power to the new vehicle, the method further includes: Record the start and end times of power adjustment for each selected vehicle, and subtract the start time of power adjustment from the end time of power adjustment to obtain the actual adjustment time. The actual adjustment time is compared with the preset standard adjustment time. When the actual adjustment time exceeds a preset multiple of the preset standard adjustment time, the selected vehicle is marked as a vehicle with abnormal response. The cumulative number of times the vehicle with abnormal response is marked within a preset historical period is counted. When the cumulative number reaches a preset abnormal number threshold, the vehicle with abnormal response is removed from the power recovery candidate queue.

6. The method of claim 1, wherein, After the step of reducing the charging power of the selected vehicle according to the optimal power recovery scheme and allocating the recovered power to the new vehicle, the method further includes: In response to charging requests from multiple new vehicles simultaneously, the difference between the total power demand of the multiple new vehicles and the current available power is calculated to obtain the total power gap; The power recovery candidate queue is divided into multiple sub-queues according to the amount of recoverable power per vehicle. The sub-queues are combined according to the total demand power and the total power gap to obtain multiple candidate power recovery combinations. For each of the candidate power recovery combinations, calculate the sum of the vehicle's sensitivity to pile position occupancy time, and select the combination with the smallest sum of sensitivity as the preferred combination; When a vehicle in the preferred combination experiences a charging interruption, a backup power deficit is calculated based on the power recovery amount of the interrupted vehicle. The vehicle with the least sensitivity to charging station occupancy time and the recoverable power that meets the backup power deficit is selected from the remaining sub-queues to serve as a replacement. The vehicles in the power recovery candidate queue are classified and labeled according to their charging status and recoverable power, and vehicles with the same charging characteristics are grouped into the same scheduling level.

7. The method of claim 6, wherein, After the step of classifying and labeling vehicles in the power recovery candidate queue according to their charging status and recoverable power, and grouping vehicles with the same charging characteristics into the same scheduling level, the method further includes: Obtain the remaining time for vehicle charging demand in each scheduling level, and divide the scheduling level into a near-offline level and a long-term online level according to the remaining time for charging demand; When the recoverable power of vehicles in the long-term on-grid category is insufficient, the ratio of recent off-grid time to power adjustment cycle is calculated, and vehicles in the recent off-grid category with a ratio greater than a preset threshold are selected to supplement power recovery.

8. A dynamic power allocation system, characterized by, The dynamic power allocation system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the dynamic power allocation system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the dynamic power allocation system, it causes the dynamic power allocation system to perform the method as described in any one of claims 1-7.

10. A computer program product, characterised in that, When the computer program product is run on the dynamic power distribution system, it causes the dynamic power distribution system to perform the method as described in any one of claims 1-7.

Images