Energy efficiency management method and system for on-street charging facilities

Abstract

The present application relates to the technical field of charging facility management, and in particular to a method and system for energy efficiency management of on-street berth charging facilities. The method includes: obtaining user reservation information and berth status information, analyzing user reservation information based on the charging berth allocation strategy and the berth status information, and determining a target berth information set; obtaining user berth selection information, and determining the basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information; obtaining a real-time regional energy efficiency status data set, and dynamically adjusting the basic charging control strategy for each vehicle in the regional berth based on the real-time regional energy efficiency status data set, and recording and outputting an energy efficiency control report. The present application makes the charging energy efficiency allocation scheme for on-street berth vehicles highly adaptable to the dynamically changing on-street berth status and grid load status, thereby realizing efficient and reasonable allocation of charging energy efficiency for vehicles parked at on-street berths.

Description

Technical Field

[0001] The present application relates to the technical field of charging facility management, and in particular to a method and system for energy efficiency management of on-street berth charging facilities. Background Art

[0002] With the promotion and popularization of new energy vehicles, the charging issue of new energy vehicles has received more and more attention, especially the problem of power replenishment of new energy vehicles in on-street parking spaces. While ensuring vehicle safety, how to improve the rationality of energy efficiency distribution during the charging process of new energy vehicles in on-street parking spaces is the core direction of improving the user experience of new energy vehicles.

[0003] However, due to the rapid changes and high uncertainty in the parking situation of on-street parking spaces, existing on-street parking space charging management technologies are unable to reasonably and efficiently allocate the charging energy efficiency of each vehicle under the above dynamic and complex circumstances, resulting in poor user experience and poor energy utilization efficiency. Summary of the Invention

[0004] The present application provides an energy efficiency management method and system for on-street charging facilities to solve the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a method for energy efficiency management of on-street parking charging facilities, the method comprising:

[0006] Obtain user reservation information and berth status information, and based on the charging berth allocation strategy and the berth status information, analyze the user reservation information to determine a target berth information set;

[0007] Obtaining user berth selection information, and determining a basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information;

[0008] A real-time regional energy efficiency status data set is obtained, and based on the real-time regional energy efficiency status data set, a basic charging control strategy for each vehicle in the regional berth is dynamically adjusted, and an energy efficiency control report is recorded and output.

[0009] Through this solution, the charging berth allocation strategy is executed according to the user reservation information and berth status information. Starting from the dual dimensions of user demand and berth status, the corresponding target berth information set is recommended to the user. Based on the user berth selection information and combined with the user reservation information, a basic charging control strategy suitable for the current user's vehicle is formulated. On this basis, the real-time regional energy efficiency status data set is further introduced. With the goal of complying with the energy efficiency status of the power grid in the region and maintaining a high coverage rate for user charging needs, the basic charging control strategy of each vehicle is dynamically adjusted, and the corresponding energy efficiency control report is provided to the corresponding regional management personnel, so that the charging energy efficiency allocation plan for on-street parking vehicles is highly adapted to the dynamically changing on-street parking status and power grid load status, realizing efficient and reasonable allocation of charging energy efficiency for on-street parking vehicles, improving users' berth usage experience, and improving energy utilization efficiency.

[0010] Optionally, the user reservation information includes a departure location, a driving destination, a charging target power level, an expected completion time, vehicle identification information, and a charging priority tag selected by the user;

[0011] The charging priority labels include emergency charging labels, regular charging labels and valley price charging labels;

[0012] The user reservation information is collected through an online reservation program, which supports smart mobile terminals and vehicle-mounted control terminals.

[0013] Through this solution, the online reservation program that supports smart mobile terminals and vehicle-mounted control terminals collects the departure location, driving destination, charging target power, vehicle identification information and charging priority tags provided by users as supporting data for berth reservation, improving the matching degree between subsequent recommended berths and user needs, while preventing the reserved on-street parking spaces from being occupied indiscriminately, and ensuring the user's berth reservation experience.

[0014] Optionally, the online reservation program includes an independent operation mode and an associated operation mode;

[0015] The associated operation mode supports the associated startup of the online reservation program from other applications associated with the user's driving purpose when the user grants permission.

[0016] Through this solution, a dual-mode architecture design of "independent operation mode + associated operation mode" is utilized for the online reservation program. The independent operation mode is used to ensure the complete availability of the independent functions of the online reservation program. The associated operation mode is used to reduce user reservation operations and improve the convenience of program use. The cross-application data automatic acquisition mechanism is used to reduce the error rate of reservation information entry, so that the user's berth selection timing can be controlled before the user arrives at the destination, thereby improving the accuracy of the subsequent berth allocation analysis process and avoiding the situation where the user temporarily searches for a berth after arriving at the destination.

[0017] Optionally, the berth status information includes berth area division information, reserved charging information, unreserved free berth distribution information and berth vehicle charging status;

[0018] The berth status information is collected by the Internet of Things on-street berth charging management device;

[0019] The IoT on-street parking charging management device includes an intelligent parking ground lock with a license plate recognition function and an intelligent charging pile that supports dynamic adjustment of output power.

[0020] Through this solution, by utilizing the architecture of "intelligent parking space ground lock with license plate recognition function + intelligent charging pile that supports dynamic adjustment of output power", the parking space area division information, reserved charging information, unreserved free parking space distribution information and parking vehicle charging status are collected as parking space status information, realizing real-time and accurate assessment of on-street parking space status.

[0021] Optionally, the step of determining a target berth information set based on a charging berth allocation strategy and analyzing the user reservation information according to the berth status information includes:

[0022] Analyzing the berth area division information according to the driving destination to determine a berth allocation target area;

[0023] Determining an estimated travel distance based on the departure location and the travel destination, and determining an estimated travel time based on the estimated travel distance;

[0024] Based on the current charging status of the berth vehicle, according to the estimated travel time and the reserved charging information, deriving the charging status of vehicles in the area after the vehicle arrives at the berth allocation target area, and determining regional vehicle charging status derivation information;

[0025] Based on the derived information of vehicle charging status in the area and according to the distribution information of unreserved free parking spaces in the current parking space allocation target area, a charging parking space allocation strategy is executed to determine a number of pre-selected target parking spaces and construct the target parking space information set.

[0026] Through this solution, based on the driving time required for the current user to reach the corresponding area, the charging status of the parking spaces in the area when the current user arrives at the corresponding area is deduced, and the derived information of the charging status of the vehicles in the area is determined. On this basis, according to the distribution information of the unreserved idle parking spaces in the current parking allocation target area, the charging parking space allocation strategy is executed, and several idle parking spaces that can meet the charging needs of the current user after arrival are pre-selected target parking spaces. A target parking space information set is constructed to prevent the mismatch between the recommended parking spaces and the user's charging needs caused by dynamically changing parking space conditions, improve the accuracy of parking space allocation analysis, and thus improve the user's parking and charging experience, providing reliable data support for subsequent energy efficiency strategy adjustments.

[0027] Optionally, the charging berth allocation strategy includes:

[0028] Based on the reserved charging information and the derived information of the regional vehicle charging status, the user vehicle is preferentially allocated to an idle berth in a local area corresponding to the berth allocation target area where the charging vehicle density is lower than a preset density range and the grid load is the lowest.

[0029] Through this solution, based on the reserved charging information and the derived information of the regional vehicle charging status, according to the two key factors of charging vehicle density and local grid load, when the charging vehicle density will not cause local grid overload, the idle berths in the local area with the lowest grid load will be used as the pre-selected target berths, effectively reducing the risk of grid overload problems caused by the spatiotemporal aggregation effect of charging load, and improving the energy efficiency and stability of the grid.

[0030] Optionally, determining a basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information includes:

[0031] Analyzing the user's berth selection information to determine the user's target berth;

[0032] Extract the corresponding ground lock unique identification code and charging pile unique identification code according to the user's target berth;

[0033] Determining a ground lock identification strategy based on the vehicle identification information and the ground lock unique identifier;

[0034] Based on the unique identification code of the charging pile, and according to the charging priority tag corresponding to the current user vehicle, a basic power allocation strategy is executed to determine the basic output power for the current user vehicle;

[0035] Constructing the basic charging control strategy according to the ground lock identification strategy and the basic output power;

[0036] The basic power allocation strategy includes:

[0037] If the charging priority tag is the emergency charging tag, obtaining a vehicle fast charging power threshold, and using the vehicle fast charging power threshold as the basic output power;

[0038] If the charging priority tag is the conventional charging tag, the default output power of the smart charging pile corresponding to the current unique identification code of the charging pile is used as the basic output power;

[0039] If the charging priority tag is the valley charging tag, obtain the grid off-peak period range and the vehicle starting charging time, simulate the gradient change of the vehicle charging power based on the vehicle starting charging time and the charging target power, and derive the vehicle charging peak period. When the vehicle charging peak period coincides with the grid off-peak period range, the corresponding vehicle charging power is used as the basic output power.

[0040] Through this solution, based on the user's target berth selected by the user as the benchmark, according to the unique identification code of the ground lock corresponding to the berth, combined with the vehicle identification information, the ground lock identification strategy used to realize the unlocking mapping between the vehicle and the corresponding berth ground lock is determined. At the same time, according to the unique identification code of the charging pile corresponding to the user's target berth, combined with the charging priority tag selected by the user, the basic power allocation strategy is executed to determine the corresponding basic output power. According to the ground lock identification strategy and the basic output power, the basic charging control strategy is constructed. Through the basic power allocation strategy, the basic power corresponding to different charging priority tags is targetedly analyzed and determined, which significantly improves the matching degree between the basic output power and the user's charging needs.

[0041] Optionally, the real-time regional energy efficiency status dataset includes real-time regional power grid dynamic load information and regional time-of-use electricity price information. Dynamically adjusting the basic charging control strategy for each vehicle in the region based on the real-time regional energy efficiency status dataset includes:

[0042] If the charging priority tag is the valley price charging tag, dynamically adjust the current vehicle's charging power gradient curve according to the valley price range in the regional time-sharing electricity price information until the moment when the vehicle's charging power reaches its peak is synchronized with the start time of the valley price period;

[0043] If the charging priority tag is the emergency charging tag, when the grid dynamic load in the real-time regional grid dynamic load information exceeds the preset load threshold, the cross-berth collaborative load reduction strategy is triggered to allocate load reduction power from other non-emergency charging vehicles in the area according to priority, and maintain the charging power of the current vehicle at the fast charging power threshold.

[0044] Through this solution, the charging power of vehicles with the charging priority label "valley price charging" is dynamically adjusted according to the low price period range in the regional time-of-use electricity price information. The time when the vehicle charging power reaches its peak is synchronized with the starting time of the low price period, preventing the local power grid load from surging due to the concentration of the vehicle power rising phase in the valley price period, thereby improving the stability of the local power grid. Through the cross-berth coordinated load reduction strategy for non-emergency charging vehicles, the demand coverage rate for emergency charging vehicles is improved.

[0045] Optionally, the cross-berth coordinated load reduction strategy includes:

[0046] Based on the expected completion time, for vehicles whose charging priority tag is not the emergency charging tag and whose remaining charging time exceeds the estimated charging time, the charging power is gradually reduced according to a preset load reduction ratio, and the released power capacity is dynamically allocated to vehicles whose charging priority tag is the emergency charging tag;

[0047] Points compensation corresponding to the power and duration of the power reduction are returned to the vehicle users who have been subjected to the power reduction. The points compensation can be used to redeem a temporary priority upgrade service or electricity fee deduction for subsequent charging services.

[0048] Through this solution, non-emergency charging vehicles with sufficient remaining charging time are subjected to gradient load reduction according to the expected completion time, and the released power capacity is dynamically allocated to vehicles with the charging priority label as emergency charging, preventing the "one-size-fits-all" load reduction strategy from significantly extending the charging time of some vehicles. At the same time, the users of vehicles affected by power load reduction are compensated with points corresponding to the load reduction power and duration, thereby improving the fairness of the charging process and thereby improving user satisfaction.

[0049] In a second aspect, the present application provides an on-street parking charging facility energy efficiency management system, the system comprising:

[0050] The berth analysis module is used to obtain user reservation information and berth status information, analyze the user reservation information based on the charging berth allocation strategy and the berth status information, and determine the target berth information set; the basic strategy analysis module is used to obtain user berth selection information, and determine the basic charging control strategy of the current vehicle based on the user berth selection information, the target berth information set and the user reservation information; the dynamic adjustment module is used to obtain a real-time regional energy efficiency status data set, and dynamically adjust the basic charging control strategy of each vehicle in the area based on the real-time regional energy efficiency status data set, and record and output an energy efficiency control report.

[0051] Optionally, in the berth analysis module, the user reservation information includes the departure location, driving destination, charging target power, expected completion time, vehicle identification information and the charging priority tag selected by the user; the charging priority tag includes an emergency charging tag, a regular charging tag and a valley charging tag; the user reservation information is collected through an online reservation program, and the online reservation program supports smart mobile terminals and vehicle-mounted control terminals.

[0052] Optionally, in the berth analysis module, the online reservation program includes an independent operation mode and an associated operation mode; the associated operation mode supports the associated launch of the online reservation program from other applications that are associated with the user's driving purpose when the user grants permission.

[0053] Optionally, in the berth analysis module, the berth status information includes berth area division information, reserved charging information, unreserved idle berth distribution information and berth vehicle charging status; the berth status information is collected through the Internet of Things on-road berth charging management device; the Internet of Things on-road berth charging management device includes an intelligent berth ground lock with license plate recognition function and an intelligent charging pile that supports dynamic adjustment of output power.

[0054] Optionally, the berth analysis module is specifically used to:

[0055] According to the driving destination, the berth area division information is analyzed to determine the berth allocation target area; according to the starting position and the driving destination, the estimated driving distance is determined, and the estimated driving time is determined based on the estimated driving distance; based on the current charging status of the berth vehicle, according to the estimated driving time and the reserved charging information, the charging status of the vehicles in the area after the vehicle arrives at the berth allocation target area is deduced to determine the regional vehicle charging status derivation information; based on the regional vehicle charging status derivation information, according to the current distribution information of unreserved idle berths in the berth allocation target area, a charging berth allocation strategy is executed to determine a number of pre-selected target berths and construct the target berth information set.

[0056] Optionally, in the berth analysis module, the charging berth allocation strategy is specifically used to:

[0057] Based on the reserved charging information and the derived information of the regional vehicle charging status, the user vehicle is preferentially allocated to an idle berth in a local area corresponding to the berth allocation target area where the charging vehicle density is lower than a preset density range and the grid load is the lowest.

[0058] Optionally, the basic strategy analysis module is specifically used to:

[0059] Analyze the user's berth selection information to determine the user's target berth; extract the corresponding ground lock unique identification code and charging pile unique identification code based on the user's target berth; determine the ground lock identification strategy based on the vehicle identification information and the ground lock unique identification; based on the charging pile unique identification code and the charging priority tag corresponding to the current user's vehicle, execute the basic power allocation strategy to determine the basic output power for the current user's vehicle; construct the basic charging control strategy based on the ground lock identification strategy and the basic output power;

[0060] The basic power allocation strategy includes:

[0061] If the charging priority tag is the emergency charging tag, obtain the vehicle's fast charging power threshold, and use the vehicle's fast charging power threshold as the basic output power; if the charging priority tag is the conventional charging tag, use the default output power of the smart charging pile corresponding to the current charging pile's unique identification code as the basic output power; if the charging priority tag is the valley charging tag, obtain the grid off-peak period range and the vehicle's starting charging time, and based on the vehicle's starting charging time and the charging target power, perform a gradient change simulation on the vehicle's charging power, derive the vehicle's charging peak period, and when the vehicle's charging peak period coincides with the grid off-peak period range, use the corresponding vehicle charging power as the basic output power.

[0062] Optionally, the dynamic adjustment module is specifically configured to:

[0063] If the charging priority tag is the valley price charging tag, the charging power gradient change curve of the current vehicle is dynamically adjusted according to the range of the low price period in the regional time-sharing electricity price information, until the moment when the vehicle charging power reaches the peak is synchronized with the starting moment of the low price period; if the charging priority tag is the emergency charging tag, when the grid dynamic load in the real-time regional grid dynamic load information exceeds the preset load threshold, the cross-berth coordinated load reduction strategy is triggered to allocate load reduction power from other non-emergency charging vehicles in the area according to priority, and maintain the charging power of the current vehicle at the fast charging power threshold.

[0064] Optionally, in the dynamic adjustment module, the cross-berth coordinated load reduction strategy is specifically used to:

[0065] According to the expected completion time, for vehicles whose charging priority tag is not the emergency charging tag and whose remaining charging time exceeds the estimated charging time, their charging power will be gradually reduced according to the preset load reduction ratio, and the released power capacity will be dynamically allocated to the vehicles whose charging priority tag is the emergency charging tag; and points compensation corresponding to the load reduction power and duration will be returned to the vehicle users who have been affected by the power load reduction. The points compensation can be used to redeem temporary priority upgrade services or electricity fee deductions for subsequent charging services. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0067] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application;

[0068] Figure 2 This is a flow chart of a method for energy efficiency management of on-street charging facilities provided in one embodiment of the present application;

[0069] Figure 3 A schematic diagram of the structure of an energy efficiency management system for on-street charging facilities provided in one embodiment of the present application. DETAILED DESCRIPTION

[0070] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0071] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0072] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0073] Because the situation of parked vehicles in on-street parking spaces changes rapidly and is highly uncertain, existing on-street parking space charging management technologies find it difficult to reasonably and efficiently allocate the charging energy efficiency of each vehicle under the above-mentioned dynamic and complex circumstances, resulting in poor user experience and poor energy utilization efficiency.

[0074] Based on this, the present application provides an energy efficiency management method and system for on-street parking charging facilities. Based on user reservation information and parking status information, a charging parking allocation strategy is executed. Starting from the dual dimensions of user demand and parking status, a corresponding target parking information set is recommended to the user. Based on the user's parking selection information and combined with the user's reservation information, a basic charging control strategy suitable for the current user's vehicle is formulated. On this basis, a real-time regional energy efficiency status data set is further introduced. With the goal of meeting the regional power grid energy efficiency status and maintaining a high coverage rate for user charging needs, the basic charging control strategy of each vehicle is dynamically adjusted, and the corresponding energy efficiency control report is provided to the corresponding regional management personnel, so that the charging energy efficiency allocation plan of on-street parking vehicles is highly adapted to the dynamically changing on-street parking status and power grid load status, realizing efficient and reasonable allocation of charging energy efficiency for on-street parking vehicles, improving the user's parking experience, and improving energy utilization efficiency.

[0075] Figure 1 This is a schematic diagram of an application scenario provided by this application. In the energy efficiency management of on-street charging facilities, the method provided by this application is applied to make the charging energy efficiency allocation plan for on-street vehicles highly adaptable to the dynamically changing on-street parking status and grid load status, achieving efficient and reasonable allocation of charging energy efficiency for on-street parking vehicles.

[0076] Specifically, the method of the present application is applied to any server, which communicates with a user device terminal, an IoT on-street parking charging management device, and a power grid monitoring system. The server obtains user reservation information provided by the user device terminal and parking status information provided by the IoT on-street parking charging management device through the server. Based on the user reservation information and parking status information, a charging parking allocation strategy is implemented. Based on the dual dimensions of user demand and parking status, a corresponding target parking information set is recommended to the user. Based on the user parking selection information and the user reservation information, a basic charging control strategy suitable for the current user's vehicle is formulated. On this basis, a real-time regional energy efficiency status dataset provided by the power grid monitoring system is further introduced. With the goal of complying with the regional power grid energy efficiency status and maintaining high coverage of user charging needs, the basic charging control strategy for each vehicle is dynamically adjusted, and the corresponding energy efficiency control report is provided to the corresponding regional management personnel. This makes the charging energy efficiency allocation plan for on-street parking vehicles highly adaptable to the dynamically changing on-street parking status and power grid load status, achieving efficient and reasonable allocation of charging energy efficiency for on-street parking vehicles, improving the user's parking experience, and improving energy utilization efficiency.

[0077] For specific implementation methods, please refer to the following embodiments.

[0078] Figure 2 This is a flow chart of a method for managing energy efficiency of on-street charging facilities provided by an embodiment of this application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes:

[0079] S201. Obtain user reservation information and berth status information, analyze the user reservation information based on the charging berth allocation strategy and the berth status information, and determine a target berth information set.

[0080] The user reservation information may be a collection of charging demand data submitted by the user through an online reservation program, and the user berth selection information may be provided by a user device terminal, such as a smart mobile device, a vehicle terminal device, etc.

[0081] The berth status information may be a data set reflecting the real-time usage status of the on-street charging berths. The berth status information may be obtained through the Internet of Things on-street berth charging management equipment installed in each berth.

[0082] The charging berth allocation strategy can be a set of berth matching rules that comprehensively considers user needs and grid status.

[0083] The target berth information set may be a candidate berth recommendation set generated based on multi-dimensional matching.

[0084] Specifically, since the on-street parking spaces are located next to public roads, car owners passing by the road can selectively park according to their own needs, resulting in two major problems in the charging energy efficiency management of on-street parking spaces: first, the parking situation of vehicles in on-street parking spaces is extremely uncertain and changes frequently; second, the charging needs of vehicles in on-street parking spaces are extremely uncertain and vary from each other. It is necessary to allocate corresponding parking spaces to users based on both user needs and parking status before the vehicle starts charging. This is because if there is no intervention at the parking space allocation stage and parking space allocation is based on the user's own temporary choice, the overall occupancy of on-street parking spaces and parking space allocation will be affected. The charging demands of vehicles in parking spaces are vague and uncontrollable, which leads to the loss of a reliable basis for the precise analysis and regulation of the charging energy efficiency of vehicles in on-street parking spaces. Through online reservation, user reservation information of users waiting to park is collected, and combined with the current parking status information, with the goal of avoiding excessive parking density in the corresponding area and keeping the power grid low load, a charging parking allocation strategy is implemented, and several parking spaces that meet user needs and the above conditions are selected as pre-selected parking spaces for users to choose from. A target parking information set is constructed to control the distribution of charging vehicles in the parking spaces from the source, providing a reliable basis for the subsequent precise analysis and regulation of the charging energy efficiency of on-street parking vehicles.

[0085] S202: Obtain user berth selection information, and determine a basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information.

[0086] The user berth selection information may be the berth information finally selected by the user in the target berth information set. The user berth selection information is provided by a user device terminal, such as a smart mobile device, a vehicle terminal device, and the like.

[0087] The basic charging control strategy may be a control strategy including charging power configuration and timing planning.

[0088] Specifically, after the user selects the corresponding berth from the target berth information set, a basic charging control strategy that is suitable for the status of the charging facilities and can meet the user's charging needs is formulated based on the charging needs reflected in the user's reservation information and the status parameters of the charging facilities in the berth selected by the user, so as to guide the basic charging process of the current user's vehicle.

[0089] S203: Acquire a real-time regional energy efficiency status data set, dynamically adjust a basic charging control strategy for each vehicle in the regional berth based on the real-time regional energy efficiency status data set, and record and output an energy efficiency control report.

[0090] The real-time regional energy efficiency status dataset may be a parameter set reflecting the energy efficiency status of power grids in different regions. The real-time regional energy efficiency status dataset may be obtained through a power grid monitoring system in the corresponding region.

[0091] The energy efficiency control report can be a comprehensive document containing monitoring data of the vehicle charging process in different berths.

[0092] Specifically, in the process of charging, the vehicles in each berth are each executing their corresponding basic charging control strategy. Due to the possibility of temporary changes in the charging demand of vehicles in different berths (for example, the user drives away the vehicle for temporary use without meeting the scheduled charging demand), which causes obvious uncertainty in the load change of the local power grid (and is also affected by other power-consuming equipment in the area). Therefore, based on the real-time regional energy efficiency status dataset, the basic charging control strategy of each vehicle in the area is dynamically adjusted as the basis for adjustment, so that the charging status of the charging vehicles in the area can maintain a high coverage rate of the user's charging demand while complying with the energy efficiency status of the regional power grid. During the adjustment process, the charging parameter change data of each vehicle is recorded in real time. Through data visualization technology, the charging parameter change data is visualized to generate a corresponding energy efficiency control report, and the corresponding energy efficiency control report is provided to the regional management personnel so that the regional management personnel can clearly control the charging status of the vehicles in the area.

[0093] Through this solution, the charging berth allocation strategy is executed according to the user reservation information and berth status information. Starting from the dual dimensions of user demand and berth status, the corresponding target berth information set is recommended to the user. Based on the user berth selection information and combined with the user reservation information, a basic charging control strategy suitable for the current user's vehicle is formulated. On this basis, the real-time regional energy efficiency status data set is further introduced. With the goal of complying with the energy efficiency status of the power grid in the region and maintaining a high coverage rate for user charging needs, the basic charging control strategy of each vehicle is dynamically adjusted, and the corresponding energy efficiency control report is provided to the corresponding regional management personnel, so that the charging energy efficiency allocation plan for on-street parking vehicles is highly adapted to the dynamically changing on-street parking status and power grid load status, realizing efficient and reasonable allocation of charging energy efficiency for on-street parking vehicles, improving users' berth usage experience, and improving energy utilization efficiency.

[0094] In some embodiments, user reservation information includes departure location, driving destination, charging target power, expected completion time, vehicle identification information and user-selected charging priority tag; charging priority tags include emergency charging tags, regular charging tags and valley charging tags; user reservation information is collected through an online reservation program, which supports smart mobile terminals and vehicle-mounted control terminals.

[0095] The departure location can be the user's current vehicle location or the geographical coordinates when the charging request is initiated. The departure location can be obtained through the positioning model in the user's terminal device.

[0096] The driving destination may be the coordinates of the next target location that the user plans to travel to. The driving destination may be manually input by the user or obtained through travel data synchronized with the vehicle navigation system.

[0097] The charging target power can be the percentage of remaining power that the user expects the vehicle to reach after charging is completed. The charging target power is set by the user according to his or her own needs.

[0098] The vehicle identification information may be a unique identifier of the current user's vehicle, such as a license plate number, and the vehicle identification information may be manually input by the user.

[0099] The charging priority tag may be tag information used to characterize the type of charging demand of the user, and the charging priority tag may be manually selected by the user.

[0100] The expected completion time may be a time when the user wishes charging to be completed.

[0101] The emergency charging tag may be a demand tag indicating that the user needs to complete charging in the shortest possible time.

[0102] The regular charging tag may be a demand tag indicating allocation of resources according to a standard charging process.

[0103] The valley price charging tag may be a demand tag indicating that a user prefers to use the low valley electricity price period.

[0104] Specifically, the combination of the departure location and the destination can accurately calculate the user's estimated driving distance, and the estimated arrival time can be derived based on real-time traffic conditions, providing a time window prediction basis for dynamic parking allocation. The demarcation of the target area for on-street parking allocation must rely on the coordinates of the driving destination to avoid parking locations too far from the user's destination, resulting in a poor user experience. The charging target power converts the user's subjective energy demand into a quantifiable energy gap value, providing target data for the formulation and adjustment of subsequent charging strategies. The expected completion time represents the length of time the user's vehicle will stay in the parking space. Vehicle identification information provides a unique user identification basis for parking reservations, preventing on-street parking from being occupied indiscriminately. The charging priority label reflects the urgency of the user's charging need. The urgent label indicates that the user has an urgent charging need and can accept the additional cost of short-term high-power charging. The regular label indicates that the user has a normal charging need and can accept the default charging mode. The valley price charging label indicates that the user has a less urgent charging need and hopes to use the grid valley price to reduce charging costs and can accept charging time delays. The above information is collected through an online reservation application that supports smart mobile terminals and in-vehicle control terminals, improving user convenience.

[0105] In other embodiments, in order to prevent users from not going to the corresponding berths for personal reasons after making a reservation, resulting in some berths being occupied for a long time by invalid reservation information, the validity period of the reservation information is set according to the estimated time of the user's arrival at the corresponding berth. When the reservation information expires, the reserved berth is automatically released.

[0106] Through this solution, the online reservation program that supports smart mobile terminals and vehicle-mounted control terminals collects the departure location, driving destination, charging target power, vehicle identification information and charging priority tags provided by users as supporting data for berth reservation, improving the matching degree between subsequent recommended berths and user needs, while preventing the reserved on-street parking spaces from being occupied indiscriminately, and ensuring the user's berth reservation experience.

[0107] In some embodiments, the online reservation program includes an independent operation mode and an associated operation mode; the associated operation mode supports the associated launch of the online reservation program from other applications that are associated with the user's driving purpose when the user grants permission.

[0108] The independent operation mode may be an operation mode based on internal data of an independent program.

[0109] The associated operation mode may be an operation mode in which data is interacted with other applications under the premise of user authorization.

[0110] Specifically, the dual-operation mode design of the online reservation program meets the different usage scenarios of users. The independent operation mode ensures the complete availability of the independent functions of the online reservation program. Users can realize the complete process of on-street parking charging through one program. The associated operation mode allows users to use other programs related to the user's driving destination, such as navigation programs, travel programs, food programs, etc. Through the associated operation mode, the online reservation program can analyze the user's destination needs in real time, and then give corresponding on-street parking recommendations, improve the user experience, and enable the user's parking selection timing to be controlled before the user arrives at the destination, improve the accuracy of the subsequent parking allocation analysis process, and avoid the situation where the user temporarily searches for a parking space after arriving at the destination; when the user starts the program for the first time, a mode selection guide page pops up, and enters the independent operation mode by default. In the associated operation mode, when it is detected that the user triggers the parking charging demand in the external application: a dynamic authorization request pop-up window is generated, listing the type of data to be shared. After the user confirms, security authentication is completed through the OAuth 2.0 protocol, and a data encryption channel is established to obtain key parameters such as the departure location, destination coordinates, and remaining power.

[0111] Through this solution, a dual-mode architecture design of "independent operation mode + associated operation mode" is utilized for the online reservation program. The independent operation mode is used to ensure the complete availability of the independent functions of the online reservation program. The associated operation mode is used to reduce user reservation operations and improve the convenience of program use. The cross-application data automatic acquisition mechanism is used to reduce the error rate of reservation information entry, so that the user's berth selection timing can be controlled before the user arrives at the destination, thereby improving the accuracy of the subsequent berth allocation analysis process and avoiding the situation where the user temporarily searches for a berth after arriving at the destination.

[0112] In some embodiments, berth status information includes berth area division information, reserved charging information, unreserved idle berth distribution information and berth vehicle charging status; berth status information is collected through the Internet of Things on-road berth charging management device; the Internet of Things on-road berth charging management device includes an intelligent berth ground lock with license plate recognition function and an intelligent charging pile that supports dynamic adjustment of output power.

[0113] The berth area division information may be division information of the management areas of different on-street berths.

[0114] The reserved charging information may be reserved information of berths in different areas.

[0115] The unreserved free berths may be distribution information of unreserved berths in different distribution information areas.

[0116] The parking space vehicle charging status may be a real-time charging parameter of vehicles in a charging state in different parking spaces.

[0117] Specifically, according to the geographical distribution characteristics of the berths in the overall area, the overall area is divided into several local areas, each of which contains a number of adjacent continuous berths, and the berth area division information is obtained. This information is used to support the fine-grained analysis of the subsequent berth allocation analysis process and improve the analysis accuracy; the reserved charging information and the distribution information of unreserved idle berths jointly reflect the berth occupancy information in different local areas; the charging status of the berth vehicle reflects the charging status of each charging vehicle in the local area, providing a regional load reference for the subsequent berth allocation analysis process; through the intelligent berth ground lock with license plate recognition function, the validity of the user reservation process is guaranteed to prevent the user's reserved berth from being temporarily occupied, and the fine-grained adjustment of the charging power is achieved through the intelligent charging pile that supports dynamic adjustment of output power.

[0118] Through this solution, by utilizing the architecture of "intelligent parking space ground lock with license plate recognition function + intelligent charging pile that supports dynamic adjustment of output power", the parking space area division information, reserved charging information, unreserved free parking space distribution information and parking vehicle charging status are collected as parking space status information, realizing real-time and accurate assessment of on-street parking space status.

[0119] In some embodiments, based on the driving destination, the berth area division information is analyzed to determine the berth allocation target area; based on the starting location and the driving destination, the estimated driving distance is determined, and based on the estimated driving distance, the estimated driving time is determined; based on the current berth vehicle charging status, according to the estimated driving time and the reserved charging information, the charging status of the vehicles in the area after the vehicle arrives at the berth allocation target area is deduced to determine the regional vehicle charging status derivation information; based on the regional vehicle charging status derivation information, according to the distribution information of the unreserved idle berths in the current berth allocation target area, the charging berth allocation strategy is executed to determine a number of pre-selected target berths and construct a target berth information set.

[0120] The estimated driving distance may be the estimated driving distance between the current user's starting location and the driving destination.

[0121] The estimated travel time may be the estimated travel time between the current user's starting location and the travel destination.

[0122] The regional vehicle charging status derivation information may be charging status information of all on-street charging vehicles in the current area after the current user arrives in the area.

[0123] The pre-selected target berth may be an on-street berth that is available for selection by the current user.

[0124] Specifically, since the vehicle parking reservation status and vehicle charging status of on-street parking spaces are constantly changing, if a corresponding parking space is recommended to the user based solely on the parking space status information in the area when the user departs for the destination, it is easy for the corresponding parking space to be suboptimal when the user arrives at the destination. For example, before the user departs, a parking space with a low density of charging vehicles is recommended to the user (the local grid load is low and can support a higher charging power). However, due to the continuous increase in the vehicle density in the area during the journey, when the user arrives at the corresponding parking space, the charging power available at the parking space is no longer able to meet the user's charging needs. This will reduce the matching rate between parking spaces and user needs, making it difficult to ensure user experience. Therefore, it is necessary to analyze the changes in parking space status in the corresponding area during the user's journey from the departure point to the destination in order to obtain reliable data that can support the implementation of the charging parking space allocation strategy. The GPS coordinates of the driving destination are parsed, and with the coordinates as the center of gravity, a candidate area within the user's walking radius is generated on the electronic map, namely the berth allocation target area. The estimated driving distance is determined based on the departure location and the driving destination through real-time navigation data, and the estimated driving time is determined based on the estimated driving distance. Based on the charging status of vehicles in different berths in the current berth allocation target area, according to the estimated driving time and reserved charging information, an LSTM neural network is applied to deduce the charging status of vehicles in the area after the vehicle arrives at the berth allocation target area, and the derived information of the regional vehicle charging status is determined. On this basis, according to the distribution information of unreserved idle berths in the current berth allocation target area, a charging berth allocation strategy is executed, and several idle berths that can meet the charging needs of the current user after arrival are pre-selected target berths to construct a target berth information set.

[0125] Through this solution, based on the driving time required for the current user to reach the corresponding area, the charging status of the parking spaces in the area when the current user arrives at the corresponding area is deduced, and the derived information of the charging status of the vehicles in the area is determined. On this basis, according to the distribution information of the unreserved idle parking spaces in the current parking allocation target area, the charging parking space allocation strategy is executed, and several idle parking spaces that can meet the charging needs of the current user after arrival are pre-selected target parking spaces. A target parking space information set is constructed to prevent the mismatch between the recommended parking spaces and the user's charging needs caused by dynamically changing parking space conditions, improve the accuracy of parking space allocation analysis, and thus improve the user's parking and charging experience, providing reliable data support for subsequent energy efficiency strategy adjustments.

[0126] In some embodiments, based on the reserved charging information and the regional vehicle charging status derivation information, the user vehicle is preferentially allocated to an idle berth in a local area where the charging vehicle density is lower than a preset density range and the grid load is the lowest within the corresponding berth allocation target area.

[0127] The charging vehicle density may be a ratio of the number of vehicles simultaneously performing charging operations to the total number of available parking spaces within the parking space allocation target area.

[0128] The preset density range may be a maximum charging vehicle density that the local power grid can accept under non-overload conditions.

[0129] The grid load may be the total output power of the grid in the region at the current moment.

[0130] Specifically, the spatiotemporal aggregation effect of charging load may cause grid overload. When the density of charging vehicles in the current local area berths increases, the spatiotemporal aggregation effect of charging load will be rapidly amplified. Therefore, when implementing the charging berth allocation strategy, the following rules need to be followed: give priority to allocating user vehicles to the idle berths in the local area where the charging vehicle density is lower than the preset density range and the grid load is the lowest within the corresponding berth allocation target area; based on the two key factors of charging vehicle density and local grid load, when the charging vehicle density will not cause local grid overload, the idle berths in the local area with the lowest grid load will be used as the pre-selected target berths.

[0131] Through this solution, based on the reserved charging information and the derived information of the regional vehicle charging status, according to the two key factors of charging vehicle density and local grid load, when the charging vehicle density will not cause local grid overload, the idle berths in the local area with the lowest grid load will be used as the pre-selected target berths, effectively reducing the risk of grid overload problems caused by the spatiotemporal aggregation effect of charging load, and improving the energy efficiency and stability of the grid.

[0132] In some embodiments, the user's berth selection information is analyzed to determine the user's target berth; based on the user's target berth, the corresponding ground lock unique identification code and charging pile unique identification code are extracted; based on the vehicle identification information and the ground lock unique identification, a ground lock identification strategy is determined; based on the charging pile unique identification code, according to the charging priority tag corresponding to the current user's vehicle, a basic power allocation strategy is executed to determine the basic output power for the current user's vehicle; based on the ground lock identification strategy and the basic output power, a basic charging control strategy is constructed; the basic power allocation strategy includes: if the charging priority tag is an emergency charging tag, obtaining the vehicle's fast charging power threshold, and using the vehicle's fast charging power threshold as the basic output power; if the charging priority tag is a conventional charging tag, using the default output power of the smart charging pile corresponding to the current charging pile unique identification code as the basic output power; if the charging priority tag is a valley charging tag, obtaining the grid off-peak period range and the vehicle start charging time, based on the vehicle start charging time and the charging target power, performing a gradient change simulation on the vehicle charging power, and deriving the vehicle charging peak period. When the vehicle charging peak period coincides with the grid off-peak period range, the corresponding vehicle charging power is used as the basic output power.

[0133] The user target berth may be a docking berth selected by the user from the target berth information set.

[0134] The unique identification code of the ground lock can be the device code of the corresponding smart ground lock in the user's target berth.

[0135] The unique identification code of the charging pile can be the device code of the corresponding smart charging pile in the user's target berth.

[0136] The ground lock identification strategy may be an identification strategy of the smart ground lock for the current vehicle.

[0137] The basic power allocation strategy may be a charging power allocation strategy of the smart charging pile for the current vehicle.

[0138] The basic output power can be the output power benchmark value of the smart charging pile for the current vehicle.

[0139] The vehicle fast charging power threshold may be the maximum charging power that the vehicle can accept in the current fast charging mode.

[0140] The default output power may be the output power of the default output mode of the smart charging pile.

[0141] The vehicle charging peak period may be a time period when the current vehicle charging power reaches a peak.

[0142] Specifically, according to the user target berth selected by the user, the unique identification code of the ground lock and the unique identification code of the charging pile in the corresponding berth are extracted by searching the device coding database, and the current vehicle identification information is used as the information identification condition for the smart ground lock corresponding to the ground lock unique identification code to change from the raised state to the lowered state, so as to determine the ground lock identification strategy and realize the unlocking mapping between the vehicle and the corresponding berth ground lock; according to the charging priority label selected by the current user, the basic power allocation strategy is executed, and the basic output power of the smart charging pile in the berth corresponding to the unique identification code of the charging pile to the current user's vehicle is adjusted; according to the ground lock identification strategy and the basic output power, a basic charging control strategy with the "identification + charging" architecture is constructed; if the charging priority label of the current vehicle is an emergency charging label, it means that the current vehicle needs short-term fast charging, and according to the user's vehicle model, the vehicle charging power data is retrieved. The database is used to determine the corresponding vehicle fast charging power threshold, and the vehicle fast charging power threshold is used as the basic output power to meet the user's fast charging needs; if the current vehicle's charging priority label is a conventional charging label, it means that the user has no additional special requirements for the charging process. At this time, the default output power of the smart charging pile can be used as the basic output power; if the current vehicle's charging priority label is a valley charging label, it means that the user wants to use valley electricity for energy replenishment to reduce charging costs. At this time, according to the vehicle's starting charging time and charging target power, the charging curves under different starting powers are simulated. When the charging peak period (the period with the largest power demand) in the current charging curve completely falls into the valley period, it means that the charging cost generated during the valley period can cover the charging cost of most users. The simulated charging power corresponding to the charging curve is used as the basic output power.

[0143] Through this solution, based on the user's target berth selected by the user as the benchmark, according to the unique identification code of the ground lock corresponding to the berth, combined with the vehicle identification information, the ground lock identification strategy used to realize the unlocking mapping between the vehicle and the corresponding berth ground lock is determined. At the same time, according to the unique identification code of the charging pile corresponding to the user's target berth, combined with the charging priority tag selected by the user, the basic power allocation strategy is executed to determine the corresponding basic output power. According to the ground lock identification strategy and the basic output power, the basic charging control strategy is constructed. Through the basic power allocation strategy, the basic power corresponding to different charging priority tags is targetedly analyzed and determined, which significantly improves the matching degree between the basic output power and the user's charging needs.

[0144] In some embodiments, if the charging priority tag is a valley charging tag, the charging power gradient change curve of the current vehicle is dynamically adjusted according to the range of the low electricity price period in the regional time-sharing electricity price information, until the moment when the vehicle charging power reaches its peak is synchronized with the start time of the low electricity price period; if the charging priority tag is an emergency charging tag, when the grid dynamic load in the real-time regional grid dynamic load information exceeds the preset load threshold, the cross-berth coordinated load reduction strategy is triggered to allocate load reduction power from other non-emergency charging vehicles in the area according to priority, and maintain the charging power of the current vehicle at the fast charging power threshold.

[0145] The real-time regional energy efficiency status dataset includes real-time regional power grid dynamic load information and regional time-of-use electricity price information.

[0146] The real-time regional power grid dynamic load information may be information reflecting the current total power demand and power supply capacity changes of the local power grid.

[0147] The regional time-of-use electricity price information may be an electricity price policy table divided by time periods and issued by the power company for the current local power grid.

[0148] The low electricity price period can be the continuous time period with the lowest electricity price in the time-of-use electricity price table.

[0149] The charging power gradient change curve may be a dynamic curve describing the change of charging power over time.

[0150] The preset load threshold may be a maximum load threshold allowed for safe operation of the power grid.

[0151] The cross-berth coordinated load reduction strategy can be a strategy that releases grid capacity to meet the needs of emergency charging vehicles by adjusting the power distribution of multiple charging vehicles.

[0152] Non-emergency charging vehicles may be vehicles with a charging priority label of a regular charging label or a valley charging label.

[0153] Load shedding power can be the amount of charging power cut from non-emergency vehicles to relieve overload pressure on the power grid.

[0154] Specifically, valley price charging users expect to complete charging during low-price periods. However, if a large number of vehicles are concentrated in the valley period and increase their power at the same time, it may cause a surge in local grid load, forming a "pseudo-peak period", which in turn increases the pressure on the grid. By simulating and adjusting the vehicle's charging power gradient change curve, its power peak moment is identified, and the deviation between the starting time of the valley period and the current vehicle power peak moment is quantified. Taking the several deviations obtained in the simulation process as the benchmark, when the current deviation is 0, it means that the time when the vehicle's charging power reaches its peak is synchronized with the starting time of the valley period. At this time, the simulated charging power corresponding to the deviation of 0 is used as the subsequent charging power for the current vehicle, realizing dynamic adjustment of the basic charging control strategy for vehicles corresponding to valley price charging tags, so that the power increase phase of different vehicles holding valley price charging tags avoids the valley period range, and their power peak moment falls within the valley period range. This reduces the user's charging cost and effectively avoids a large number of vehicles concentrating in the valley period and increasing their power at the same time, thus ensuring the stable operation of the grid.

[0155] Emergency charging vehicles require continuous high-power input, but when the grid load is close to the upper limit, directly meeting their needs may lead to regional power outage risks. When the dynamic load of the grid in the real-time regional grid dynamic load information exceeds the preset load threshold, all charging vehicles in the area are traversed, and vehicles with charging priority labels such as conventional charging labels or valley charging labels are screened. A cross-berth coordinated load reduction strategy is implemented for these vehicles, and the charging power of these vehicles is gradually reduced in fixed steps until the vacant grid load can meet the charging needs of emergency charging vehicles in the area, so that the charging power of vehicles that need emergency charging is maintained at its corresponding fast charging power threshold.

[0156] Through this solution, the charging power of vehicles with the charging priority label "valley price charging" is dynamically adjusted according to the low price period range in the regional time-of-use electricity price information. The time when the vehicle charging power reaches its peak is synchronized with the starting time of the low price period, preventing the local power grid load from surging due to the concentration of the vehicle power rising phase in the valley price period, thereby improving the stability of the local power grid. Through the cross-berth coordinated load reduction strategy for non-emergency charging vehicles, the demand coverage rate for emergency charging vehicles is improved.

[0157] In some embodiments, based on the expected completion time, for vehicles whose charging priority tags are not emergency charging tags and whose remaining charging time exceeds the estimated charging time, their charging power is gradually reduced according to a preset load reduction ratio, and the released power capacity is dynamically allocated to vehicles whose charging priority tags are emergency charging tags; points compensation corresponding to the load reduction power and duration are returned to the vehicle users who have been affected by the power reduction, and the points compensation is used to redeem temporary priority upgrade services or electricity fee deductions for subsequent charging services.

[0158] The remaining charging time may be the remaining charging time that the vehicle can be parked in the berth, determined based on the current time and the expected completion time in the user's reservation information.

[0159] The estimated charging time may be the charging time required for the current vehicle to meet the corresponding charging requirements.

[0160] The preset load reduction ratio may be a preset amplitude ratio of each load reduction of the vehicle power during the gradient load reduction process.

[0161] The temporary priority boost may be a temporary permission that the user can activate to prioritize power allocation during subsequent charging processes.

[0162] Specifically, if a "one-size-fits-all" approach is adopted during the load reduction adjustment for non-emergency charging vehicles (such as uniformly reducing the power of all non-emergency vehicles), the charging time for some vehicles will be significantly extended. Users are extremely sensitive to the fairness of charging services. Such measures will cause user dissatisfaction and cause some vehicles to occupy parking spaces for a long time due to extended charging times, making it impossible for subsequent users to reserve and use parking spaces. The remaining charging time for each non-emergency charging vehicle is determined based on the expected completion time. If the current vehicle is a non-emergency charging vehicle and its corresponding charging time exceeds the estimated charging time, it means that the current vehicle has sufficient parking time for charging. At this time, its charging power is gradually reduced according to the preset load reduction ratio, and the released power capacity is dynamically allocated to vehicles with the charging priority tag of emergency charging. To further ensure the fairness of the charging process, through an online reservation process, points compensation corresponding to the load reduction power and duration are returned to the users of vehicles affected by the load reduction. The points compensation can be used to redeem temporary priority upgrade services or electricity fee deductions for subsequent charging services to improve user satisfaction.

[0163] Through this solution, non-emergency charging vehicles with sufficient remaining charging time are subjected to gradient load reduction according to the expected completion time, and the released power capacity is dynamically allocated to vehicles with the charging priority label as emergency charging, preventing the "one-size-fits-all" load reduction strategy from significantly extending the charging time of some vehicles. At the same time, the users of vehicles affected by power load reduction are compensated with points corresponding to the load reduction power and duration, thereby improving the fairness of the charging process and thereby improving user satisfaction.

[0164] Figure 3 This is a structural diagram of an energy efficiency management system for on-street parking charging facilities provided in one embodiment of the present application, such as Figure 3 As shown, an on-street parking charging facility energy efficiency management system 300 of this embodiment includes: a parking analysis module 301 , a basic strategy analysis module 302 and a dynamic adjustment module 303 .

[0165] The berth analysis module 301 is used to obtain user reservation information and berth status information, analyze the user reservation information based on the charging berth allocation strategy and the berth status information, and determine the target berth information set; the basic strategy analysis module 302 is used to obtain user berth selection information, and determine the basic charging control strategy of the current vehicle based on the user berth selection information, the target berth information set and the user reservation information; the dynamic adjustment module 303 is used to obtain a real-time regional energy efficiency status data set, and dynamically adjust the basic charging control strategy of each vehicle in the area based on the real-time regional energy efficiency status data set, and record and output an energy efficiency control report.

[0166] Optionally, in the berth analysis module 301, the user reservation information includes the departure location, the driving destination, the charging target power, the expected completion time, the vehicle identification information and the charging priority tag selected by the user; the charging priority tag includes an emergency charging tag, a regular charging tag and a valley charging tag; the user reservation information is collected through an online reservation program, and the online reservation program supports smart mobile terminals and vehicle-mounted control terminals.

[0167] Optionally, in the berth analysis module 301, the online reservation program includes an independent operation mode and an associated operation mode; the associated operation mode supports the associated startup of the online reservation program from other applications that are associated with the user's driving purpose when the user grants permission.

[0168] Optionally, in the berth analysis module 301, the berth status information includes berth area division information, reserved charging information, unreserved idle berth distribution information and berth vehicle charging status; the berth status information is collected by the Internet of Things on-road berth charging management device; the Internet of Things on-road berth charging management device includes an intelligent berth ground lock with license plate recognition function and an intelligent charging pile that supports dynamic adjustment of output power.

[0169] Optionally, the berth analysis module 301 is specifically configured to:

[0170] According to the driving destination, the berth area division information is analyzed to determine the berth allocation target area; according to the starting position and the driving destination, the estimated driving distance is determined, and the estimated driving time is determined based on the estimated driving distance; based on the current charging status of the berth vehicle, according to the estimated driving time and the reserved charging information, the charging status of the vehicles in the area after the vehicle arrives at the berth allocation target area is deduced to determine the regional vehicle charging status derivation information; based on the regional vehicle charging status derivation information, according to the current distribution information of unreserved idle berths in the berth allocation target area, a charging berth allocation strategy is executed to determine a number of pre-selected target berths and construct the target berth information set.

[0171] Optionally, in the berth analysis module 301, the charging berth allocation strategy is specifically used to:

[0172] Based on the reserved charging information and the derived information of the regional vehicle charging status, the user vehicle is preferentially allocated to an idle berth in a local area corresponding to the berth allocation target area where the charging vehicle density is lower than a preset density range and the grid load is the lowest.

[0173] Optionally, the basic strategy analysis module 302 is specifically configured to:

[0174] Analyze the user's berth selection information to determine the user's target berth; extract the corresponding ground lock unique identification code and charging pile unique identification code based on the user's target berth; determine the ground lock identification strategy based on the vehicle identification information and the ground lock unique identification; based on the charging pile unique identification code and the charging priority tag corresponding to the current user's vehicle, execute the basic power allocation strategy to determine the basic output power for the current user's vehicle; construct the basic charging control strategy based on the ground lock identification strategy and the basic output power;

[0175] The basic power allocation strategy includes:

[0176] If the charging priority tag is the emergency charging tag, obtain the vehicle's fast charging power threshold, and use the vehicle's fast charging power threshold as the basic output power; if the charging priority tag is the conventional charging tag, use the default output power of the smart charging pile corresponding to the current charging pile's unique identification code as the basic output power; if the charging priority tag is the valley charging tag, obtain the grid off-peak period range and the vehicle's starting charging time, and based on the vehicle's starting charging time and the charging target power, perform a gradient change simulation on the vehicle's charging power, derive the vehicle's charging peak period, and when the vehicle's charging peak period coincides with the grid off-peak period range, use the corresponding vehicle charging power as the basic output power.

[0177] Optionally, the dynamic adjustment module 303 is specifically configured to:

[0178] If the charging priority tag is the valley price charging tag, the charging power gradient change curve of the current vehicle is dynamically adjusted according to the range of the low price period in the regional time-sharing electricity price information, until the moment when the vehicle charging power reaches the peak is synchronized with the starting moment of the low price period; if the charging priority tag is the emergency charging tag, when the grid dynamic load in the real-time regional grid dynamic load information exceeds the preset load threshold, the cross-berth coordinated load reduction strategy is triggered to allocate load reduction power from other non-emergency charging vehicles in the area according to priority, and maintain the charging power of the current vehicle at the fast charging power threshold.

[0179] Optionally, in the dynamic adjustment module 303, the cross-berth coordinated load reduction strategy is specifically used to:

[0180] According to the expected completion time, for vehicles whose charging priority tag is not the emergency charging tag and whose remaining charging time exceeds the estimated charging time, their charging power will be gradually reduced according to the preset load reduction ratio, and the released power capacity will be dynamically allocated to the vehicles whose charging priority tag is the emergency charging tag; and points compensation corresponding to the load reduction power and duration will be returned to the vehicle users who have been affected by the power load reduction. The points compensation can be used to redeem temporary priority upgrade services or electricity fee deductions for subsequent charging services.

[0181] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A method for energy efficiency management of on-street charging facilities, characterized in that: include: Obtain user reservation information and berth status information, and based on the charging berth allocation strategy and the berth status information, analyze the user reservation information to determine a target berth information set; Obtaining user berth selection information, and determining a basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information; Obtain a real-time regional energy efficiency status dataset, dynamically adjust a basic charging control strategy for each vehicle in the regional berth based on the real-time regional energy efficiency status dataset, and record and output an energy efficiency control report; The user reservation information includes the departure location, driving destination, charging target power, expected completion time, vehicle identification information and the charging priority tag selected by the user; The charging priority labels include emergency charging labels, regular charging labels and valley price charging labels; The user reservation information is collected through an online reservation program, which supports smart mobile terminals and vehicle-mounted control terminals; The berth status information includes berth area division information, reserved charging information, unreserved vacant berth distribution information and berth vehicle charging status; The berth status information is collected by the Internet of Things on-street berth charging management device; The IoT on-street parking charging management device includes a smart parking ground lock with license plate recognition function and a smart charging pile that supports dynamic adjustment of output power; The method of determining a target berth information set based on a charging berth allocation strategy and analyzing the user reservation information according to the berth status information includes: Analyzing the berth area division information according to the driving destination to determine a berth allocation target area; Determining an estimated travel distance based on the departure location and the travel destination, and determining an estimated travel time based on the estimated travel distance; Based on the current charging status of the berth vehicle, according to the estimated travel time and the reserved charging information, deriving the charging status of vehicles in the area after the vehicle arrives at the berth allocation target area, and determining regional vehicle charging status derivation information; Based on the derived information of vehicle charging status in the area and according to the distribution information of unreserved free parking spaces in the current parking space allocation target area, a charging parking space allocation strategy is executed to determine a number of pre-selected target parking spaces and construct the target parking space information set.

2. The method according to claim 1, characterized in that The online reservation program includes an independent operation mode and an associated operation mode; The associated operation mode supports the associated startup of the online reservation program from other applications associated with the user's driving purpose when the user grants permission.

3. The method according to claim 1, characterized in that The charging berth allocation strategy includes: Based on the reserved charging information and the derived information of the regional vehicle charging status, the user vehicle is preferentially allocated to an idle berth in a local area corresponding to the berth allocation target area where the charging vehicle density is lower than a preset density range and the grid load is the lowest.

4. The method according to claim 3, characterized in that The determining of a basic charging control strategy for the current vehicle based on the user berth selection information, the target berth information set, and the user reservation information includes: Analyzing the user's berth selection information to determine the user's target berth; Extract the corresponding ground lock unique identification code and charging pile unique identification code according to the user's target berth; Determining a ground lock identification strategy based on the vehicle identification information and the ground lock unique identifier; Based on the unique identification code of the charging pile, and according to the charging priority tag corresponding to the current user vehicle, a basic power allocation strategy is executed to determine the basic output power for the current user vehicle; Constructing the basic charging control strategy according to the ground lock identification strategy and the basic output power; The basic power allocation strategy includes: If the charging priority tag is the emergency charging tag, obtaining a vehicle fast charging power threshold, and using the vehicle fast charging power threshold as the basic output power; If the charging priority tag is the conventional charging tag, the default output power of the smart charging pile corresponding to the current unique identification code of the charging pile is used as the basic output power; If the charging priority tag is the valley charging tag, obtain the grid off-peak period range and the vehicle starting charging time, simulate the gradient change of the vehicle charging power based on the vehicle starting charging time and the charging target power, and derive the vehicle charging peak period. When the vehicle charging peak period coincides with the grid off-peak period range, the corresponding vehicle charging power is used as the basic output power.

5. The method according to claim 4, characterized in that The real-time regional energy efficiency status data set includes real-time regional power grid dynamic load information and regional time-of-use electricity price information. The dynamic adjustment of the basic charging control strategy for each vehicle in the region based on the real-time regional energy efficiency status data set includes: If the charging priority tag is the valley price charging tag, dynamically adjust the current vehicle's charging power gradient curve according to the valley price range in the regional time-sharing electricity price information until the moment when the vehicle's charging power reaches its peak is synchronized with the start time of the valley price period; If the charging priority tag is the emergency charging tag, when the grid dynamic load in the real-time regional grid dynamic load information exceeds the preset load threshold, the cross-berth collaborative load reduction strategy is triggered to allocate load reduction power from other non-emergency charging vehicles in the area according to priority, and maintain the charging power of the current vehicle at the fast charging power threshold.

6. The method according to claim 5, characterized in that The cross-berth coordinated load reduction strategy includes: Based on the expected completion time, for vehicles whose charging priority tag is not the emergency charging tag and whose remaining charging time exceeds the estimated charging time, the charging power is gradually reduced according to a preset load reduction ratio, and the released power capacity is dynamically allocated to vehicles whose charging priority tag is the emergency charging tag; Points compensation corresponding to the power and duration of the power reduction are returned to the vehicle users who have been subjected to the power reduction. The points compensation can be used to redeem a temporary priority upgrade service or electricity fee deduction for subsequent charging services.

7. An energy efficiency management system for on-street berth charging facilities, characterized in that: The method according to any one of claims 1 to 6 comprises: A berth analysis module is used to obtain user reservation information and berth status information, analyze the user reservation information based on the berth status information based on the charging berth allocation strategy, and determine a target berth information set; A basic strategy analysis module is used to obtain user parking space selection information and determine a basic charging control strategy for the current vehicle based on the user parking space selection information, the target parking space information set, and the user reservation information; The dynamic adjustment module is used to obtain a real-time regional energy efficiency status data set, dynamically adjust the basic charging control strategy of each vehicle in the area based on the real-time regional energy efficiency status data set, and record and output an energy efficiency control report.

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