A smart charging pile peak-valley time-adjusting charging energy storage system and method

Abstract

This invention discloses an intelligent peak-valley time-of-use charging energy storage system and method for charging piles, relating to the field of charging piles. It includes a charging pile area time-of-use load preset module, a multi-power supply mode dynamic identification and division module, a vehicle demand analysis module, an intelligent charging queue scheduling module, a neighboring pile collaborative monitoring and recommendation module, and an interactive management platform. The system dynamically monitors the load peaks in the area where the charging pile group is located, constructs a three-level dynamic time-of-use charging pile group power supply mode rule library (peak, valley, and peak periods), performs real-time analysis of the demand of vehicles waiting to be charged within the charging pile group, implements an emergency charging demand identification and priority response mechanism, screens vehicles within peak and valley periods, and prioritizes vehicle demands. Through power load equalization and basic guaranteed charging strategies, the charging pile group can serve more low-battery vehicles at the same time. Simultaneously, the intelligent recommendation function guides users to nearby charging piles with lower loads, improving service fairness and user satisfaction.

Description

Technical Field

[0001] This invention relates to the field of charging piles, specifically to an intelligent peak-valley time-adjusting charging energy storage system and method for charging piles. Background Technology

[0002] With the accelerated global energy structure transformation, electric vehicles have become a key path for energy conservation and emission reduction in the transportation sector. The widespread adoption and centralized charging of electric vehicles have placed unprecedented pressure on the planning, operation, and safety of existing power distribution networks. The high degree of uncertainty in charging load in time and space easily overlaps with traditional peak residential and commercial electricity consumption, resulting in a significant peak-on-peak effect. This can lead to a series of safety problems such as transformer overload, increased line losses, and voltage exceeding limits, severely restricting the grid's capacity and operational economy. Current mainstream commercial charging pile management systems typically have power control functions based on preset schedules. Operators pre-set charging power limits or rates for different times based on peak and off-peak periods published by the grid. This approach has significant drawbacks: First, the peak and off-peak periods used are static and fixed, unable to respond to real-time, dynamically changing load fluctuations in the grid. A sudden, unplanned regional load spike cannot be identified and responded to by the preset model, still posing an overload risk. Second, its control strategy is crude, applying a "one-size-fits-all" approach to all vehicles, lacking differentiated and personalized service capabilities for users with urgent needs, such as vehicles whose batteries are about to run out.

[0003] This application aims to monitor the total load of the area where the charging pile cluster is located in real time, dynamically monitor sudden and instantaneous load peaks in the area, and construct a three-level dynamic time period power supply mode rule library for the charging pile cluster. This reduces the peak load pressure on the power grid, performs real-time analysis of the demand of vehicles waiting to be charged within the charging pile cluster, and implements an emergency charging demand identification and priority response mechanism. It screens vehicles within peak and off-peak periods and prioritizes responding to their needs. Through power load equalization and basic guarantee charging strategies, the charging pile cluster can serve more low-battery vehicles at the same time, improving the service frequency and asset utilization per unit time. This ensures that car owners whose batteries are about to run out can receive timely assistance. At the same time, the intelligent recommendation function guides users to nearby charging piles with lower loads, achieving load balancing among multiple charging stations in the area and significantly improving service fairness and user satisfaction. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent peak-valley time-adjusting charging energy storage system and method for charging piles, so as to solve the problems in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A charging pile intelligent peak-valley time-of-use regulation charging energy storage system includes a charging pile area time-of-use load preset module, a multi-power supply mode dynamic identification and division module, a vehicle demand analysis module, an execution charging queue intelligent scheduling module, a neighboring pile collaborative monitoring and recommendation module, and an interactive management platform.

[0007] The charging pile area time-of-use power load preset module obtains the peak and valley time intervals of the power grid to set the initial time period. According to different initial time periods, the power supply load of the charging pile group in the monitoring area is preset, and the total power load in the set area of ​​the charging pile is collected in real time.

[0008] The multi-power supply mode dynamic identification and division module compares the total power load of the historical charging piles in the set area within the statistically limited time interval with multiple thresholds, analyzes the historical load data, automatically identifies the load peak pattern, forms a dynamic time period division model including peak hours, valley hours and three levels, and builds a multi-mode power supply rule library for charging pile groups under different levels of time periods.

[0009] The vehicle demand analysis module obtains the charging information of the vehicles requesting charging, analyzes the charging demand of the vehicles, compares the vehicle's battery level with a set battery threshold, and prioritizes the allocation of power resources to vehicles with too low a battery threshold.

[0010] The intelligent scheduling module for the charging queue analyzes the remaining available load capacity of the charging pile group in the current time period based on the power supply mode of different time periods, and makes multi-dimensional judgments on charging requests. If the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, the module performs intelligent collaborative scheduling analysis of charging volume for charging vehicles.

[0011] The neighboring charging pile collaborative monitoring and recommendation module obtains the power supply load of the monitored charging pile group in the current time period. When the power supply load is saturated, it searches for geographically nearby charging piles, obtains the real-time remaining available load of the neighboring piles, and intelligently pushes the optimal low-load neighboring piles.

[0012] Further settings: The charging pile area time-sharing power load preset module includes an initial time period power load predefinition submodule and a location area power load real-time monitoring and acquisition submodule. The initial time period power load predefinition submodule obtains the peak and valley time periods set by the local power grid, defines them as the basic time period mode, determines the precise start and end times of each peak and valley time period, and uploads them to the interactive management platform. The location area power load real-time monitoring and acquisition submodule includes an area distance setting unit and a load monitoring unit. The area distance setting unit is centered on the charging pile group, and the administrator sets a fixed area range for delineation, which is then sent to the load monitoring unit. The load monitoring unit is connected to several smart meters, screens the smart meters within the set area range, and collects the total power load data of the set area range in real time by manually preset different sampling periods. The collected raw data is validated, obvious outliers are removed, and the real-time total load data summarized by different sampling periods and their corresponding timestamps are uploaded and backed up.

[0013] Further configuration: The multi-power supply mode dynamic identification and segmentation module includes a multi-time period refined dynamic identification and segmentation sub-module and a multi-mode power consumption rule base construction sub-module. The multi-time period refined dynamic identification and segmentation sub-module obtains real-time total load data within different sampling periods, pre-screens sampling periods within peak time period intervals, and when a sampling period belongs to a peak time period interval, analyzes and compares the real-time total load data of the monitored set area range, comparing the real-time total load data of the set area range with the set load peak threshold, where the set load peak threshold is initialized by the administrator. When a certain sampling period belongs to a peak time period interval, and the real-time total load data of the set area range within that sampling period is greater than the set load peak threshold, the current sampling period is marked as peak power consumption, the sampling periods marked as peak power consumption are obtained, and the sampling periods marked as peak power consumption are preprocessed for time intervals to screen fixed peak time period intervals.

[0014] Further settings: The multi-period refined dynamic identification and segmentation submodule filters out any sampling period marked as peak electricity consumption, divides the current sampling period into several short-period periods, and obtains the total electricity load data of the set area range within several short-period periods through the location area electricity load real-time monitoring and acquisition submodule. If the total electricity load data of the set area range in all short-period periods is greater than the set load peak threshold, the current sampling period is determined to be the actual peak electricity consumption time interval. If the short-period period is continuously... The load drops to less than or equal to the set peak load threshold within one cycle. Within the current sampling period, short-term intervals with load peak values ​​less than or equal to a set threshold are removed, resulting in the actual peak electricity consumption time intervals after the removal. All actual peak electricity consumption time intervals are aggregated, and the start and end times of each interval are marked, creating a historical actual peak electricity consumption time interval database. The administrator sets the time statistics period, dividing each day into 24 time slices. A machine learning engine is used to analyze the frequency of peak electricity consumption within these 24 time slices. The number of days in the time statistics period is set as follows. The number of peak-hour electricity consumption events within the set statistical period for each time slice is: The frequency of power consumption at each time point is calculated as follows: , When the frequency of peak electricity consumption exceeds a set number, it is marked as a significant fixed peak time slot. The continuity of these marked fixed peak time slots is determined, and consecutive significant fixed peak time slots are merged into a fixed peak time period. The daily fixed peak time period intervals, peak time period intervals, and valley time period intervals are summarized. The multi-mode electricity consumption rule database construction module uploads the updated fixed peak time period intervals, peak time period intervals, and valley time period intervals to build a time period rule database. Based on the power operation limit coefficients and corresponding maximum power supply loads of the fixed peak time period intervals, peak time period intervals, and valley time period intervals pre-set by the interactive management platform, the peak power supply load is... Peak power load Off-peak power supply load.

[0015] Further configuration: The vehicle charging demand analysis module includes a vehicle charging demand identification and marking submodule and a priority charging resource allocation submodule. The vehicle charging demand marking submodule obtains the charging requests of different vehicles within the currently monitored charging pile group, and simultaneously obtains the charging demand information of different vehicles, including vehicle license plate number, the corresponding time period for charging, the vehicle's current battery level, battery capacity, minimum guaranteed battery level, and maximum charging power, and calculates the requested charging amount for different vehicles. The priority charging resource allocation submodule obtains the remaining battery level of different vehicles waiting to be charged. When the remaining battery level is less than a set low battery level threshold, the vehicle is determined to be a vehicle with an emergency charging demand. The set low battery level threshold is calculated based on 10% of the corresponding vehicle's battery capacity. Vehicles with emergency charging demand are prioritized and marked. The current vehicles with emergency charging demand are extracted to form a priority charging queue. The priority charging queue is sorted according to the remaining battery level of the vehicles with emergency charging demand and inserted at the top of the charging queue for priority allocation of charging resources.

[0016] Further configuration: The intelligent scheduling module for the charging queue includes a sub-module for energy storage load redistribution scheduling and analysis and a sub-module for monitoring the power demand of the execution queue. The sub-module for energy storage load redistribution scheduling and analysis includes a remaining available load capacity monitoring unit and a charging power redistribution unit. The remaining available load capacity monitoring unit pre-determines the time period in which the monitored charging pile group is located. When the monitored charging group is in a peak time period, it detects and calculates the remaining available power load capacity of the charging pile group in real time during the current peak time period. It identifies whether there is a priority charging queue in the queue to be charged and determines whether the remaining available power load capacity is greater than the total charging load required by vehicles with emergency charging needs in the priority charging queue. If the remaining available power load capacity is greater than or equal to the total charging load required by vehicles with emergency charging needs in the priority charging queue, it prioritizes charging for vehicles with emergency charging needs within the priority charging queue. If the remaining available power load capacity is less than the total charging load required by vehicles with emergency charging needs in the priority charging queue, it sends the priority charging queue, the total charging load required by the priority charging queue, and the remaining available power load capacity for the current time period to the charging power redistribution unit, and simultaneously sends a signal to the interactive management platform to refuse to accept new vehicle charging requests.

[0017] Further settings: The charging power redistribution unit extracts and monitors vehicles charging within the charging pile group. The administrator can pre-set the power baseline threshold through the interactive management platform, select vehicles that are charging and whose real-time power is greater than the set power baseline threshold, interrupt the charging power load of the selected vehicles, send a pause charging notification to the selected vehicle owner, and re-estimate the current remaining available power load capacity.

[0018] Extract vehicles with emergency charging needs from the priority charging queue, obtain the minimum guaranteed battery capacity for each vehicle with emergency charging needs in the priority charging queue, and set the minimum guaranteed battery capacity for different vehicles with emergency charging needs in the priority charging queue as follows: , , ... Set the re-estimated current remaining available power supply capacity as follows: The minimum guaranteed battery capacity for vehicles with different emergency charging needs The system charges each vehicle with an emergency charging need according to its minimum guaranteed battery level. Once a vehicle reaches its minimum guaranteed battery level, charging is temporarily suspended, and the vehicle at the top of the priority charging queue continues charging until its remaining battery level exceeds a set low battery threshold. Simultaneously, the suspended charging vehicles are marked. (The sentence about minimum guaranteed battery levels for different emergency charging needs is incomplete and requires further context.) The system extracts the minimum guaranteed power of vehicles with emergency charging needs according to the priority charging queue order until it is closest to the re-estimated current remaining available power load capacity. These vehicles are marked as pre-extracted vehicles, and the minimum guaranteed power of the pre-extracted vehicles is used to charge them. When a pre-extracted vehicle reaches its minimum guaranteed power, charging of that emergency charging vehicle is temporarily suspended. The released power load is used to charge the vehicles in the priority charging queue that have not been extracted according to their minimum guaranteed power. This process continues until all emergency charging vehicles in the priority charging queue reach their minimum guaranteed power. Then, the emergency charging vehicle at the top of the priority charging queue is extracted and continues to be charged. If the remaining power is greater than the set low power threshold, the vehicles whose charging has been suspended are marked.

[0019] When a vehicle finishes charging and leaves the monitored charging pile group, the remaining available power supply capacity is reassessed by the remaining available load capacity monitoring unit. Power supply resources are allocated in sequence to vehicles in the priority charging queue that have temporarily suspended charging after the minimum guaranteed charging, until the vehicle's power reaches the power benchmark threshold. When there is no priority charging queue in the monitored charging pile group, vehicles whose real-time power is greater than the set power benchmark threshold and which have temporarily suspended charging are restored to normal power charging according to the vehicle charging access order.

[0020] Further settings: The execution queue power demand monitoring submodule obtains the power demand of different vehicles connected to the charging pile group in real time, summarizes it, and sends it to the interactive management platform.

[0021] Further configuration: The neighboring charging pile collaborative monitoring and recommendation module includes a sub-module for acquiring the real-time load status of nearby charging piles and a sub-module for optimal recommendation of low-load charging piles. The sub-module for acquiring the real-time load status of nearby charging piles takes the monitored charging pile group as the center and collects the real-time remaining available load of charging piles in the set nearby range of the monitored charging pile group. If it finds that the remaining load of a nearby charging pile is greater than the set load threshold, it obtains all charging vehicles marked as temporarily suspended in the monitored charging pile group within the current time period. The sub-module for optimal recommendation of low-load charging piles obtains the vehicle owner information of the charging vehicles marked as temporarily suspended and generates nearby charging pile recommendation information, which is sent to the interactive management platform. The nearby charging pile recommendation information includes the location, distance, current remaining available load capacity, and estimated travel time of the nearby charging piles.

[0022] A method for intelligent peak-valley time-based charging and energy storage of charging piles:

[0023] S1: Use the charging pile area time-sharing power load preset module to obtain the peak and valley time intervals of the power grid for initial time setting, and preset the power supply load of the charging pile group in the monitoring area according to different initial time periods, while collecting the total power load in the set area of ​​the charging pile in real time.

[0024] S2: The multi-power supply mode dynamic identification and division module compares the total power load of the historical charging piles in the set area within the statistically limited time interval with multiple thresholds, analyzes the historical load data, automatically identifies the load peak pattern, forms a dynamic time period division model including peak hours, valley hours and three levels, and builds a multi-mode power supply rule library for charging pile groups under different levels of time periods.

[0025] S3: Use the demand analysis module for vehicles waiting to be charged to obtain charging information of vehicles requesting charging, analyze the charging demand of vehicles, set a power threshold for comparison of vehicle power, and give priority to allocating power resources to vehicles with too low power thresholds.

[0026] S4: Utilize the intelligent scheduling module for the charging queue to analyze the remaining available load capacity of the charging pile group in the current time period based on the power supply mode of different time periods, and make multi-dimensional judgments on charging requests. If the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, intelligent collaborative scheduling analysis of charging volume will be performed on the charging vehicles.

[0027] S5: Utilize the neighboring charging pile collaborative monitoring and recommendation module to obtain the power supply load of the monitored charging pile group during the current time period. When the power supply load is saturated, search for geographically nearby charging piles, obtain the real-time remaining available load of the neighboring piles, and intelligently push the optimal low-load neighboring piles.

[0028] Compared with existing technologies, the beneficial effects of this invention are as follows: It aims to monitor the total load of the area where the charging pile cluster is located in real time, dynamically monitor sudden and instantaneous load peaks in the area where the charging pile cluster is located, construct a three-level dynamic time period power supply mode rule library for the charging pile cluster (peak, valley, and peak), reduce the peak load pressure on the power grid, perform real-time analysis of the demand of vehicles waiting to be charged within the charging pile cluster, implement an emergency charging demand identification and priority response mechanism, screen within peak and peak periods, prioritize response to vehicle demand, and through power load equalization and basic guarantee charging strategies, enable the charging pile cluster to serve more low-battery vehicles at the same time, improve the service frequency and asset utilization rate per unit time, ensure that car owners whose batteries are about to run out can receive timely assistance, and at the same time, the intelligent recommendation function guides users to nearby charging piles with lower loads, realizing load balancing among multiple charging stations in the area, significantly improving service fairness and user satisfaction. Attached Figure Description

[0029] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0030] Figure 1 This is a schematic diagram illustrating the specific implementation process of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles according to the present invention;

[0031] Figure 2 This invention relates to a module of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles. Figure 1 ;

[0032] Figure 3 This invention relates to a module of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles. Figure 2 ;

[0033] Figure 4 This invention relates to a module of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles. Figure 3 ;

[0034] Figure 5 This invention relates to a module of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles. Figure 4 ;

[0035] Figure 6 This invention relates to a module of an intelligent peak-valley time-adjusting charging and energy storage system for charging piles. Figure 5 ;

[0036] Figure 7 This is a flowchart illustrating the steps of an intelligent peak-valley time-adjusting charging and energy storage method for charging piles according to the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1: Please refer to Figures 1-6 In this embodiment of the invention, a charging pile intelligent peak-valley time-of-use regulation charging energy storage system is provided. The system includes a charging pile area time-of-use power load preset module, a multi-power supply mode dynamic identification and division module, a vehicle demand analysis module, an execution charging queue intelligent scheduling module, a neighboring pile collaborative monitoring and recommendation module, and an interactive management platform.

[0039] The charging pile area time-of-use power load preset module obtains the peak and valley time intervals of the power grid to set the initial time period. According to different initial time periods, the power supply load of the charging pile group in the monitoring area is preset, and the total power load in the set area of ​​the charging pile is collected in real time.

[0040] like Figure 2As shown, further explanation is needed. The charging pile area time-sharing power load preset module includes an initial time period power load preset sub-module and a location area power load real-time monitoring and acquisition sub-module. The initial time period power load preset sub-module obtains the peak and valley time periods set by the local power grid, defines them as the basic time period mode, determines the precise start and end times of each peak and valley time period, and uploads them to the interactive management platform. The location area power load real-time monitoring and acquisition sub-module includes an area distance setting unit and a load monitoring unit. The area distance setting unit delineates a fixed area range centered on the charging pile group, as set by the administrator, and sends it to the load monitoring unit. The load monitoring unit is connected to several smart meters, screens the smart meters within the set area range, and collects the total power load data of the set area range in real time by manually presetting different sampling periods. The collected raw data is validated, obvious outliers are removed, and the real-time total load data summarized by different sampling periods and their corresponding timestamps are uploaded and backed up.

[0041] The multi-power supply mode dynamic identification and division module compares the total power load of the historical charging piles in the set area within the statistically limited time interval with multiple thresholds, analyzes the historical load data, automatically identifies the load peak pattern, forms a dynamic time period division model including peak hours, valley hours and three levels, and builds a multi-mode power supply rule library for charging pile groups under different levels of time periods.

[0042] like Figure 3 As shown, further explanation is needed. The multi-power supply mode dynamic identification and division module includes a multi-time period refined dynamic identification and division sub-module and a multi-mode power consumption rule base construction sub-module. The multi-time period refined dynamic identification and division sub-module obtains real-time total load data within different sampling periods, pre-screens sampling periods within peak time period intervals, and analyzes and compares the real-time total load data of the monitored set area range when the sampling period belongs to the peak time period interval. The real-time total load data of the set area range is compared with the set load peak threshold, where the set load peak threshold is initialized by the administrator. When a certain sampling period belongs to the peak time period interval and the real-time total load data of the set area range within the sampling period is greater than the set load peak threshold, the current sampling period is marked as peak power consumption. The sampling periods marked as peak power consumption are obtained, and the sampling periods marked as peak power consumption are preprocessed for time intervals to screen fixed peak time period intervals.

[0043] To further explain, the multi-period refined dynamic identification and segmentation submodule filters out any sampling period marked as peak electricity consumption, divides the current sampling period into several short-period periods, and obtains the total electricity load data of a set area range within several short-period periods through the location area electricity load real-time monitoring and acquisition submodule. If the total electricity load data of the set area range in all short-period periods is greater than the set load peak threshold, the current sampling period is determined to be the actual peak electricity consumption time interval. If the short-period period is continuously... The load drops to less than or equal to the set peak load threshold within one cycle. Within the current sampling period, short-term intervals with load peak values ​​less than or equal to a set threshold are removed, resulting in the actual peak electricity consumption time intervals after the removal. All actual peak electricity consumption time intervals are aggregated, and the start and end times of each interval are marked, creating a historical actual peak electricity consumption time interval database. The administrator sets the time statistics period, dividing each day into 24 time slices. A machine learning engine is used to analyze the frequency of peak electricity consumption within these 24 time slices. The number of days in the time statistics period is set as follows. The number of peak-hour electricity consumption events within the set statistical period for each time slice is: The frequency of power consumption at each time point is calculated as follows: , When the frequency of electricity consumption during a certain time period exceeds a set number, it is marked as a significant fixed peak time period. It is then determined whether the marked significant fixed peak time periods are continuous. Continuous significant fixed peak time periods are merged into fixed peak time periods. The fixed peak time period intervals, peak time period intervals, and valley time period intervals are summarized in the daily data.

[0044] The multi-mode electricity consumption rule library construction submodule uploads updated fixed peak hour time intervals, off-peak hour time intervals, and time-sharing intervals to build a time-sharing rule database. Based on the power operation limit coefficients and corresponding maximum power supply loads for the fixed peak hour time intervals and off-peak hour time intervals pre-set by the user on the interactive management platform, the peak hour power supply load... Peak power load Off-peak power supply load.

[0045] The vehicle demand analysis module obtains the charging information of the vehicles requesting charging, analyzes the charging demand of the vehicles, compares the vehicle's battery level with a set battery threshold, and prioritizes the allocation of power resources to vehicles with too low a battery threshold.

[0046] like Figure 4As shown, further explanation is needed. The vehicle charging demand analysis module includes a vehicle charging demand identification and marking submodule and a priority charging resource allocation submodule. The vehicle charging demand marking submodule obtains the charging requests of different vehicles within the currently monitored charging pile group, and simultaneously obtains the charging demand information of different vehicles, including vehicle license plate number, the corresponding time period for charging, the vehicle's current battery level, battery capacity, minimum guaranteed battery level, and maximum charging power. It calculates the requested charging amount for different vehicles. The priority charging resource allocation submodule obtains the remaining battery level of different vehicles waiting to be charged. When the remaining battery level is less than a set low battery level threshold, the vehicle is determined to be a vehicle with an emergency charging demand. The set low battery level threshold is calculated based on 10% of the corresponding vehicle's battery capacity. Vehicles with emergency charging demand are prioritized and marked. The current vehicles with emergency charging demand are extracted to form a priority charging queue. The priority charging queue is sorted according to the remaining battery level of the vehicles with emergency charging demand and inserted at the top of the charging queue for priority allocation of charging resources.

[0047] The intelligent scheduling module for the charging queue analyzes the remaining available load capacity of the charging pile group in the current time period based on the power supply mode of different time periods, and makes multi-dimensional judgments on charging requests. If the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, the module performs intelligent collaborative scheduling analysis of charging volume for charging vehicles.

[0048] like Figure 5 As shown, it should be further explained that the intelligent scheduling module for the charging queue includes a storage load redistribution scheduling analysis submodule and a queue power demand monitoring submodule. The storage load redistribution scheduling analysis submodule includes a remaining available load capacity monitoring unit and a charging power redistribution unit. The remaining available load capacity monitoring unit pre-determines the time period in which the monitored charging pile group is located. When the monitored charging group is in a peak time period, it detects and calculates the remaining available power load capacity of the charging pile group in real time during the current peak time period. It identifies whether there is a priority charging queue in the queue to be charged and determines whether the remaining available power load capacity is greater than the total charging load required by vehicles with emergency charging needs in the priority charging queue. If the remaining available power load capacity is greater than or equal to the total charging load required by vehicles with emergency charging needs in the priority charging queue, it prioritizes charging vehicles with emergency charging needs within the priority charging queue. If the remaining available power load capacity is less than the total charging load required by vehicles with emergency charging needs in the priority charging queue, it sends the priority charging queue, the total charging load required by the priority charging queue, and the remaining available power load capacity for the current time period to the charging power redistribution unit, and simultaneously sends a signal to the interactive management platform to refuse to accept new vehicle charging requests.

[0049] It needs to be explained in detail that the charging power redistribution unit extracts and monitors the vehicles that are charging in the charging pile group. The administrator can pre-set the power reference threshold through the interactive management platform, select the vehicles that are charging and whose real-time power is greater than the set power reference threshold, interrupt the charging power load of the selected vehicles, send a notification message to the owner of the selected vehicles to temporarily suspend charging, and re-estimate the current remaining available power load capacity.

[0050] Extract vehicles with emergency charging needs from the priority charging queue, obtain the minimum guaranteed battery capacity for each vehicle with emergency charging needs in the priority charging queue, and set the minimum guaranteed battery capacity for different vehicles with emergency charging needs in the priority charging queue as follows: , , ... Set the re-estimated current remaining available power supply capacity as follows: The minimum guaranteed battery capacity for vehicles with different emergency charging needs The system charges each vehicle with an emergency charging need according to its minimum guaranteed battery level. Once a vehicle reaches its minimum guaranteed battery level, charging is temporarily suspended, and the vehicle at the top of the priority charging queue continues charging until its remaining battery level exceeds a set low battery threshold. Simultaneously, the suspended charging vehicles are marked. (The sentence about minimum guaranteed battery levels for different emergency charging needs is incomplete and requires further context.) The system extracts the minimum guaranteed power of vehicles with emergency charging needs according to the priority charging queue order until it is closest to the re-estimated current remaining available power load capacity. These vehicles are marked as pre-extracted vehicles, and the minimum guaranteed power of the pre-extracted vehicles is used to charge them. When a pre-extracted vehicle reaches its minimum guaranteed power, charging of that emergency charging vehicle is temporarily suspended. The released power load is used to charge the vehicles in the priority charging queue that have not been extracted according to their minimum guaranteed power. This process continues until all emergency charging vehicles in the priority charging queue reach their minimum guaranteed power. Then, the emergency charging vehicle at the top of the priority charging queue is extracted and continues to be charged. If the remaining power is greater than the set low power threshold, the vehicles whose charging has been suspended are marked.

[0051] When a vehicle finishes charging and leaves the monitored charging pile group, the remaining available power supply capacity is reassessed by the remaining available load capacity monitoring unit. Power supply resources are allocated in sequence to vehicles in the priority charging queue that have temporarily suspended charging after the minimum guaranteed charging, until the vehicle's power reaches the power benchmark threshold. When there is no priority charging queue in the monitored charging pile group, vehicles whose real-time power is greater than the set power benchmark threshold and which have temporarily suspended charging are restored to normal power charging according to the vehicle charging access order.

[0052] The execution queue power demand monitoring submodule obtains the power demand of different vehicles connected to the charging pile group in real time, summarizes it, and sends it to the interactive management platform.

[0053] The neighboring charging pile collaborative monitoring and recommendation module obtains the power supply load of the monitored charging pile group in the current time period. When the power supply load is saturated, it searches for geographically nearby charging piles, obtains the real-time remaining available load of the neighboring piles, and intelligently pushes the optimal low-load neighboring piles.

[0054] like Figure 6 As shown, further explanation is needed. The neighboring charging pile collaborative monitoring and recommendation module includes a sub-module for obtaining the real-time load status of neighboring charging piles and a sub-module for optimal recommendation of low-load charging piles. The sub-module for obtaining the real-time load status of neighboring charging piles takes the monitored charging pile group as the center and collects the real-time remaining available load of charging piles in the set nearby range of the monitored charging pile group. If it finds that the remaining load of a neighboring charging pile is greater than the set load threshold, it obtains all charging vehicles marked as temporarily suspended in the monitored charging pile group during the current time period. The sub-module for optimal recommendation of low-load charging piles obtains the vehicle owner information of the charging vehicles marked as temporarily suspended and generates neighboring charging pile recommendation information, which is sent to the interactive management platform. The neighboring charging pile recommendation information includes the location, distance, current remaining available load capacity, and estimated travel time of the neighboring charging piles.

[0055] Example 2: See Figure 7 A method for intelligent peak-valley time-based charging and energy storage of charging piles:

[0056] S1: Use the charging pile area time-sharing power load preset module to obtain the peak and valley time intervals of the power grid for initial time setting, and preset the power supply load of the charging pile group in the monitoring area according to different initial time periods, while collecting the total power load in the set area of ​​the charging pile in real time.

[0057] S2: The multi-power supply mode dynamic identification and division module compares the total power load of the historical charging piles in the set area within the statistically limited time interval with multiple thresholds, analyzes the historical load data, automatically identifies the load peak pattern, forms a dynamic time period division model including peak hours, valley hours and three levels, and builds a multi-mode power supply rule library for charging pile groups under different levels of time periods.

[0058] S3: Use the demand analysis module for vehicles waiting to be charged to obtain charging information of vehicles requesting charging, analyze the charging demand of vehicles, set a power threshold for comparison of vehicle power, and give priority to allocating power resources to vehicles with too low power thresholds.

[0059] S4: Utilize the intelligent scheduling module for the charging queue to analyze the remaining available load capacity of the charging pile group in the current time period based on the power supply mode of different time periods, and make multi-dimensional judgments on charging requests. If the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, intelligent collaborative scheduling analysis of charging volume will be performed on the charging vehicles.

[0060] S5: Utilize the neighboring charging pile collaborative monitoring and recommendation module to obtain the power supply load of the monitored charging pile group during the current time period. When the power supply load is saturated, search for geographically nearby charging piles, obtain the real-time remaining available load of the neighboring piles, and intelligently push the optimal low-load neighboring piles.

[0061] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A smart peak-valley time-adjusting charging and energy storage system for charging piles, characterized in that: The system includes: Charging pile area time-of-use power load preset module: acquires the peak and valley time intervals of the power grid to set the initial time period, presets the power supply load of the charging pile group in the monitoring area according to different initial time periods, and collects the total power load in the set area of ​​the charging pile in real time. Multi-power supply mode dynamic identification and division module: Based on the total power load of historical charging piles in the designated area collected within the statistically limited time interval, multi-threshold comparison is performed to analyze historical load data, automatically identify load peak patterns, form a dynamic time period division model including peak hours, valley hours and three levels, and construct a multi-mode power supply rule library for charging pile groups under different time periods. The demand analysis module for vehicles waiting to be charged: obtains charging information of vehicles requesting charging, analyzes the charging demand of vehicles, sets a power threshold for comparison of vehicle power, and prioritizes the allocation of power resources to vehicles with too low power thresholds. The intelligent scheduling module for the charging queue is executed: based on the power supply mode of different time periods, it analyzes the remaining available load capacity of the charging pile group in the current time period, makes multi-dimensional judgments on charging requests, and if the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, it performs intelligent collaborative scheduling analysis of charging volume for charging vehicles. Neighboring charging pile collaborative monitoring and recommendation module: obtains the power supply load of the monitored charging pile group in the current time period. When the power supply load is saturated, it searches for geographically nearby charging piles, obtains the real-time remaining available load of the neighboring piles, and intelligently pushes the optimal low-load neighboring piles. The multi-power supply mode dynamic identification and division module includes a multi-time period refined dynamic identification and division sub-module and a multi-mode power consumption rule base construction sub-module. The multi-time period refined dynamic identification and division sub-module obtains real-time total load data within different sampling periods, pre-screens sampling periods within peak time period intervals, and when a sampling period belongs to a peak time period interval, analyzes and compares the real-time total load data of the monitored set area range, and compares the real-time total load data of the set area range with the set load peak threshold, wherein the set load peak threshold is initialized by the administrator. When a certain sampling period belongs to a peak time period interval, and the real-time total load data of the set area range within the sampling period is greater than the set load peak threshold, the current sampling period is marked as peak power consumption, the sampling period marked as peak power consumption is obtained, the sampling period marked as peak power consumption is preprocessed for time interval, and the fixed peak time period interval is screened. The multi-mode electricity consumption rule library construction submodule uploads updated fixed peak hour time intervals, off-peak hour time intervals, and time-sharing intervals to build a time-sharing rule database. Based on the power operation limit coefficients and corresponding maximum power supply loads for the fixed peak hour time intervals and off-peak hour time intervals pre-set by the user on the interactive management platform, the peak hour power supply load... Peak power load Off-peak power supply load.

2. The intelligent peak-valley time-adjusting charging and energy storage system for charging piles according to claim 1, characterized in that... The charging pile area time-segmented power load preset module includes an initial time-segment power load preset submodule and a location area power load real-time monitoring and acquisition submodule. The initial time-segment power load preset submodule obtains the peak and valley time intervals set by the local power grid, defines them as the basic time period mode, determines the precise start and end times of each peak and valley time interval, and uploads them to the interactive management platform. The location area power load real-time monitoring and acquisition submodule includes an area distance setting unit and a load monitoring unit. The area distance setting unit delineates a fixed area range centered on the charging pile group, as set by the administrator, and sends it to the load monitoring unit. The load monitoring unit is connected to several smart meters, screens the smart meters within the set area range, and collects the total power load data of the set area range in real time by manually presetting different sampling periods. The collected raw data is validated, obvious outliers are removed, and the real-time total load data summarized by different sampling periods and their corresponding timestamps are uploaded and backed up.

3. The intelligent peak-valley time-of-use charging and energy storage system for charging piles according to claim 1, characterized in that... The multi-period refined dynamic identification and segmentation submodule filters out any sampling period marked as peak electricity consumption, divides the current sampling period into several short-period periods, and obtains the total electricity load data of a set area range within several short-period periods through the location area electricity load real-time monitoring and acquisition submodule. If the total electricity load data of the set area range in all short-period periods is greater than the set load peak threshold, the current sampling period is determined to be the actual peak electricity consumption time interval. If the short-period period is continuously... The load drops to less than or equal to the set peak load threshold within one cycle. Within the current sampling period, short-term intervals with load peak values ​​less than or equal to a set threshold are removed, resulting in the actual peak electricity consumption time intervals after the removal. All actual peak electricity consumption time intervals are aggregated, and the start and end times of each interval are marked, creating a historical actual peak electricity consumption time interval database. The administrator sets the time statistics period, dividing each day into 24 time slices. A machine learning engine is used to analyze the frequency of peak electricity consumption within these 24 time slices. The number of days in the time statistics period is set as follows. The number of peak-hour electricity consumption events within the set statistical period for each time slice is: The frequency of power consumption at each time point is calculated as follows: , When the frequency of electricity consumption during a certain time period exceeds a set number, it is marked as a significant fixed peak time period. It is then determined whether the marked significant fixed peak time periods are continuous. Continuous significant fixed peak time periods are merged into fixed peak time periods. The fixed peak time period intervals, peak time period intervals, and valley time period intervals are summarized in the daily data.

4. The intelligent peak-valley time-of-use charging and energy storage system for charging piles according to claim 1, characterized in that... The vehicle charging demand analysis module includes a vehicle charging demand identification and marking submodule and a priority charging resource allocation submodule. The vehicle charging demand marking submodule acquires the charging requests of different vehicles within the currently monitored charging pile group, and simultaneously acquires the charging demand information of different vehicles, including vehicle license plate number, the corresponding time period for charging, the vehicle's current battery level, battery capacity, minimum guaranteed battery level, and maximum charging power, and calculates the requested charging amount for different vehicles. The priority charging resource allocation submodule acquires the remaining battery level of different vehicles waiting to be charged. When the remaining battery level is less than a set low battery level threshold, the vehicle is determined to be an emergency charging demand vehicle. The set low battery level threshold is calculated based on 10% of the corresponding vehicle's battery capacity. Emergency charging demand vehicles are prioritized and extracted to form a priority charging queue. The priority charging queue is sorted according to the remaining battery level of the emergency charging demand vehicles and inserted at the top of the charging queue for priority allocation of charging resources.

5. The intelligent peak-valley time-adjusting charging and energy storage system for charging piles according to claim 1, characterized in that... The intelligent scheduling module for the charging queue includes a storage load redistribution scheduling and analysis submodule and a queue power demand monitoring submodule. The storage load redistribution scheduling and analysis submodule includes a remaining available load capacity monitoring unit and a charging power redistribution unit. The remaining available load capacity monitoring unit pre-determines the time period in which the monitored charging pile group is located. When the monitored charging group is in a peak time period, it detects and calculates the remaining available power load capacity of the charging pile group in real time during the current peak time period. It identifies whether there is a priority charging queue in the queue to be charged and determines whether the remaining available power load capacity is greater than the total charging load required by vehicles with emergency charging needs in the priority charging queue. If the remaining available power load capacity is greater than or equal to the total charging load required by vehicles with emergency charging needs in the priority charging queue, it prioritizes charging vehicles with emergency charging needs within the priority charging queue. If the remaining available power load capacity is less than the total charging load required by vehicles with emergency charging needs in the priority charging queue, it sends the priority charging queue, the total charging load required by the priority charging queue, and the remaining available power load capacity for the current time period to the charging power redistribution unit, and simultaneously sends a signal to the interactive management platform to refuse to receive new vehicle charging requests.

6. The intelligent peak-valley time-of-use regulating charging and energy storage system for charging piles according to claim 5, characterized in that... The charging power redistribution unit extracts and monitors vehicles charging within the charging pile group. The administrator presets a power reference threshold through the interactive management platform, selects vehicles that are charging and whose real-time power is greater than the preset power reference threshold, interrupts the charging power load of the selected vehicle, sends a pause charging notification to the owner of the selected vehicle, and re-estimates the current remaining available power load capacity. Extract vehicles with emergency charging needs from the priority charging queue, obtain the minimum guaranteed battery capacity for each vehicle with emergency charging needs in the priority charging queue, and set the minimum guaranteed battery capacity for different vehicles with emergency charging needs in the priority charging queue as follows: , , ... Set the re-estimated current remaining available power supply capacity as follows: The minimum guaranteed battery capacity for vehicles with different emergency charging needs The system charges each vehicle with an emergency charging need according to its minimum guaranteed battery level. Once a vehicle reaches its minimum guaranteed battery level, charging is temporarily suspended, and the vehicle at the top of the priority charging queue continues charging until its remaining battery level exceeds a set low battery threshold. Simultaneously, the suspended charging vehicles are marked. (The sentence about minimum guaranteed battery levels for different emergency charging needs is incomplete and requires further context.) The system extracts the minimum guaranteed power of vehicles with emergency charging needs according to the priority charging queue order until it is closest to the re-estimated current remaining available power load capacity. These vehicles are marked as pre-extracted vehicles, and the minimum guaranteed power of the pre-extracted vehicles is used to charge them. When a pre-extracted vehicle reaches its minimum guaranteed power, charging of that emergency charging vehicle is temporarily suspended. The released power load is used to charge the vehicles in the priority charging queue that have not been extracted according to their minimum guaranteed power. This process continues until all emergency charging vehicles in the priority charging queue reach their minimum guaranteed power. Then, the emergency charging vehicle at the top of the priority charging queue is extracted and continues to be charged. If the remaining power is greater than the set low power threshold, the vehicles whose charging has been suspended are marked. When a vehicle finishes charging and leaves the monitored charging pile group, the remaining available power supply capacity is reassessed by the remaining available load capacity monitoring unit. Power supply resources are allocated in sequence to vehicles in the priority charging queue that have temporarily suspended charging after the minimum guaranteed charging, until the vehicle's power reaches the power benchmark threshold. When there is no priority charging queue in the monitored charging pile group, vehicles whose real-time power is greater than the set power benchmark threshold and which have temporarily suspended charging are restored to normal power charging according to the vehicle charging access order.

7. The intelligent peak-valley time-adjusting charging and energy storage system for charging piles according to claim 5, characterized in that... The execution queue power demand monitoring submodule acquires and summarizes the power demand of different vehicles connected to the charging pile group in real time, and sends it to the interactive management platform.

8. The intelligent peak-valley time-of-use charging and energy storage system for charging piles according to claim 1, characterized in that... The neighboring charging pile collaborative monitoring and recommendation module includes a real-time load status acquisition submodule for nearby charging piles and an optimal recommendation submodule for low-load charging piles. The real-time load status acquisition submodule for nearby charging piles takes the monitored charging pile group as the center and collects the real-time remaining available load of charging piles in the set nearby range of the monitored charging pile group. If it finds that the remaining load of a certain nearby charging pile is greater than the set load threshold, it obtains all charging vehicles marked as temporarily suspended in the monitored charging pile group in the current time period. The optimal recommendation submodule for low-load charging piles obtains the vehicle owner information of the charging vehicles marked as temporarily suspended and generates nearby charging pile recommendation information, which is sent to the interactive management platform. The nearby charging pile recommendation information includes the location, distance, current remaining available load capacity and estimated travel time of the nearby charging piles.

9. A method for intelligent peak-valley time-based charging and energy storage of charging piles, used in the intelligent peak-valley time-based charging and energy storage system for charging piles as described in any one of claims 1-8, characterized in that... : S1: Use the charging pile area time-sharing power load preset module to obtain the peak and valley time intervals of the power grid for initial time setting, and preset the power supply load of the charging pile group in the monitoring area according to different initial time periods, while collecting the total power load in the set area of ​​the charging pile in real time. S2: The multi-power supply mode dynamic identification and division module compares the total power load of the historical charging piles in the set area within the statistically limited time interval with multiple thresholds, analyzes the historical load data, automatically identifies the load peak pattern, forms a dynamic time period division model including peak hours, valley hours and three levels, and builds a multi-mode power supply rule library for charging pile groups under different levels of time periods. S3: Use the demand analysis module for vehicles waiting to be charged to obtain charging information of vehicles requesting charging, analyze the charging demand of vehicles, set a power threshold for comparison of vehicle power, and give priority to allocating power resources to vehicles with too low power thresholds. S4: Utilize the intelligent scheduling module for the charging queue to analyze the remaining available load capacity of the charging pile group in the current time period based on the power supply mode of different time periods, and make multi-dimensional judgments on charging requests. If the charging demand of vehicles in the priority charging queue is greater than the remaining available load capacity, intelligent collaborative scheduling analysis of charging volume will be performed on the charging vehicles. S5: Utilize the neighboring charging pile collaborative monitoring and recommendation module to obtain the power supply load of the monitored charging pile group during the current time period. When the power supply load is saturated, search for geographically nearby charging piles, obtain the real-time remaining available load of the neighboring piles, and intelligently push the optimal low-load neighboring piles.

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