Intelligent management system and method for charging equipment

Abstract

The invention relates to the technical field of charging equipment management, and discloses a charging equipment intelligent management system and method, and the specific steps are as follows: constructing an intelligent management system comprising a charging station information unit, a charging equipment information unit and a user information unit, setting a charging equipment recommendation platform, and recommending a nearby charging station to a user. The method comprises the following steps: recording a search event of a user, collecting position information of a charging station, a use state of charging equipment and electric quantity data, dividing a monitoring area and monitoring search points to identify peak and low peak time periods, and executing a charging equipment supplement strategy and a charging station matching strategy to optimize distribution of the charging equipment and charging selection of the user. The method comprises the following steps: collecting search points of each monitoring area in a monitoring time period, executing a charging equipment supplement strategy, and in addition, executing a charging station matching strategy by a system according to personal information data collected in a peak time period.

Description

Technical Field

[0001] The present invention relates to the technical field of charging equipment management technology, and in particular to an intelligent management system and method for charging equipment. Background Art

[0002] With the popularity of electric vehicles and portable electronic devices, the management and optimization of charging equipment has become an increasingly important issue. The uneven distribution of charging equipment, low efficiency, and uncertainty in charging demand have brought many inconveniences to users and also posed challenges to the stable operation of the power grid. Existing charging equipment management methods often rely on static charging station layouts and manual scheduling, lack real-time monitoring and intelligent response to user charging behavior, and are difficult to adapt to the rapid changes in user demand and dynamic fluctuations in power grid load.

[0003] Traditional charging equipment management methods do not fully utilize the Internet of Things technology and cannot achieve real-time status monitoring and intelligent scheduling of charging equipment, resulting in a waste of charging resources and a decline in user charging experience. In addition, existing technologies are also insufficient in processing large-scale charging data, realizing charging demand forecasting, and optimizing charging resource allocation, and cannot provide effective decision-making support for charging equipment operators.

[0004] In the field of intelligent charging equipment management, how to achieve real-time monitoring, accurate evaluation and intelligent scheduling of the use status of charging equipment to improve the use efficiency of charging equipment and the charging experience of users is a technical problem that needs to be solved urgently. Existing technologies often ignore the charging habits and power usage characteristics of individual users, and lack personalized services and refined management.

[0005] Therefore, developing a method for using a charging equipment intelligent management system to achieve real-time monitoring, dynamic analysis and intelligent management of charging equipment usage data has become an important research direction in the field of intelligent charging equipment management. This new method needs to be able to accurately collect charging equipment usage data, deeply analyze user charging behavior, accurately predict charging demand trends, and provide personalized charging recommendations and services to users and charging equipment operators to improve the efficiency of charging equipment use and the user's charging experience. Summary of the invention

[0006] The present invention provides a charging equipment intelligent management system and method, which are used to promote solving the problems mentioned in the above background technology.

[0007] The present invention provides the following technical solutions: a charging equipment intelligent management system and method, Optionally, a charging station information unit, a charging device information unit and a user information unit are set; Recommend charging stations to users through the charging equipment recommendation platform; The charging station information unit is used to store the location information of the charging station and the number of charging devices in the charging station; The charging device information unit is used to collect the usage status of the charging device and the power of the charging device; The charging equipment usage status is divided into the to-be-allocated status and the allocated status; The user information unit is used to store the personal information data of the user when using the charging device recommendation platform; The personal information data includes, when a search event occurs, if the user agrees that the system will take the personal information data, the user's search time and the user's last three search addresses will be obtained; If the user does not agree that the system uses personal information data, the system will recommend the nearest charging equipment to the user based on the user's current geographical location; Optionally, if the user searches for a nearby charging station through the charging device recommendation platform, this event is recorded as a search event; Obtain the locations of all charging stations, divide them into monitoring areas, and monitor the monitoring areas according to the monitoring time intervals; During the monitoring period, the number of search points in each monitoring area is obtained through the charging equipment recommendation platform; According to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located, obtain the peak time period and the off-peak time period of each monitoring area in the monitoring time cycle; Execute charging equipment replenishment strategy based on peak and off-peak time periods in all monitoring areas; The charging station matching strategy is implemented based on the personal information data collected by the charging equipment recommendation platform during the peak time periods of all monitoring areas.

[0008] Optionally, the acquiring the locations of all charging stations, dividing the monitoring areas, and monitoring the monitoring areas according to the monitoring time intervals includes: According to the location of the charging station, a circular area with a radius of 3 kilometers is delineated with the charging station as the center point, and the circular area is marked as the monitoring area; Get the locations of all charging stations and group the marked monitoring areas into a set, recorded as set A; Set monitoring time period; The monitoring cycle is set to one week, and each cycle is divided into seven monitoring time periods, namely Monday, Tuesday...Sunday; In each monitoring period, set the monitoring time interval, which is 2h; According to the monitoring time interval, the 24 hours of a day are divided into 12 sub-monitoring time periods, which are respectively recorded as the first time period, the second time period ... the twelfth time period.

[0009] Optionally, obtaining the number of search points in each monitoring area through the charging device recommendation platform during the monitoring time period includes: During the sub-monitoring time period, monitoring the user's search events on the charging device recommendation platform; The search event is that the user searches for nearby charging stations in the charging equipment recommendation platform; If a search event occurs in the monitoring area, the search points of the monitoring area are accumulated once, and the accumulated value is 1; If the user uses the charging equipment of a charging station once in the monitoring area, the search points of the monitoring area will be accumulated once, and the accumulated value is 1; When entering the next sub-monitoring time period, the search points in the monitoring area will be reset and counted again.

[0010] Optionally, obtaining the number of peak search points and the number of low peak search points in each monitoring time period in the monitoring time cycle according to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located, includes: Obtain the number of search points corresponding to each sub-monitoring time period in the monitoring time period; According to the temporal order of the sub-monitoring time periods, the search points of the sub-monitoring time periods are recorded as the first peak value, the second peak value, ... the twelfth peak value; Sort the first peak, the second peak, ... the twelfth peak in descending order according to the number of search points to form a sequence; Select the top three search points in the sequence to form a set, which is recorded as the target peak search point set; Select the last three search points in the sequence to form a set, which is recorded as the target low-peak search point set; Obtain the number of charging devices in the monitoring area, and filter the elements in the target peak search point set and the target low peak search point set respectively. The filtering steps are as follows: In the target peak search point set, if the search point number is greater than the number of charging devices in the monitoring area, the time period is marked as the peak time period of the monitoring area; In the target low-peak search point set, if the search point number is less than the number of charging devices in the monitoring area , then the time period is marked as the low-peak time period of the monitoring area.

[0011] Optionally, executing a charging equipment replenishment strategy according to peak time periods and off-peak time periods of all monitoring areas includes: The charging equipment replenishment strategy is: S1: According to the peak time period of the monitoring area, determine whether the sub-monitoring time periods of other monitoring areas are marked as off-peak time periods; If a sub-monitoring time period of a monitoring area is marked as a low-peak time period, the monitoring area is marked as a supplementary equipment area; The charging equipment in the supplementary equipment area supplements the charging equipment in the monitoring area during the peak time period, and returns the supplemented charging equipment after the peak time period ends; S2: If the monitoring area is in the peak time period and no monitoring area is in the off-peak time period, then at the beginning of the next monitoring cycle, a charging device is added to the monitoring area; The number of newly added charging devices = the number of target peak search points - the number of charging devices in the monitoring area.

[0012] Optionally, executing a charging station matching strategy according to the personal information data collected by the charging equipment recommendation platform during the peak time period of all monitoring areas includes: At the beginning of the next monitoring cycle, all monitoring areas with peak time periods in the previous monitoring cycle are obtained and grouped to form a first monitoring area group; Acquire adjacent monitoring areas of each first monitoring area in the first monitoring area set, and form a second monitoring area set; Wherein the elements in the first monitoring region set correspond to certain elements in the second monitoring region set; According to the first monitoring area set, all monitoring areas in the set are monitored; The monitoring interval during peak hours is set to 15 minutes, and monitoring is performed every 15 minutes. During each monitoring process, the charging equipment recommendation platform collects the user's personal information data; According to the personal information data, obtain the number of search events of the user in each monitoring area within the first monitoring area set, and the number of charging devices remaining in the monitoring area; If the number of search events in the monitoring area is less than the number of remaining charging devices in the monitoring area, the monitoring area is recommended to the user for charging; If the number of search events in the monitoring area is greater than the number of remaining charging devices in the monitoring area, the user who triggered the search event is obtained according to the personal information data to form a set, which is recorded as the first user set; According to the users in the first user set, the location information of all users is obtained, and the distance between the charging station and the user is calculated to form a sequence, and the sequence is sorted from small to large, and the sorted sequence is recorded as a first sequence; A charging station matching strategy is executed according to the first user set and the first sequence.

[0013] Optionally, executing the charging station matching strategy according to the first user set and the first sequence includes: S3: Obtain the last three search addresses and location information of users in the first user set; S4: based on the last three search addresses and the user's location information, obtain a route between each search address and the user's current location; S5: Obtaining location information of elements in the second monitoring area set, and if the route passes through elements in the second monitoring area set, recommending the elements in the monitoring area and the first monitoring area set to the user; If the user selects a monitoring area in the second monitoring area set, the user is removed from the first user set and the first sequence; S6: If the number of elements in the first user set after elimination is greater than the number T of remaining charging devices of the corresponding elements in the first monitoring area set, then according to the first sequence after elimination, in order of the user's distance to the charging station in the first monitoring area, the corresponding elements in the first monitoring area set are recommended to the user for charging in sequence from near to far, until the remaining charging devices at the charging station are zero; S7: If there is a user in the first user set who is not recommended the corresponding element in the first monitoring area set, recommend the user to select the corresponding charging station in the second monitoring area set for charging.

[0014] The present invention has the following beneficial effects: 1. The system using the intelligent management method of charging equipment realizes the management of the location of the charging station, the status of the charging equipment and the personal information of the user by constructing the charging station information unit, the charging equipment information unit and the user information unit. According to the real-time information of the charging station and the specific needs of the user, the system recommends the appropriate charging station for charging. Through the charging equipment recommendation platform, the system analyzes the user's search time, location information and historical search address to provide the user with personalized charging station recommendations. The charging equipment information unit collects the usage status and power information of the charging equipment, so that the system can adjust the allocation strategy of the charging equipment according to the pending allocation status and the allocated status of the equipment.

[0015] 2. The intelligent management method for charging equipment records the user's search events and obtains the user's charging needs in real time. By dividing the monitoring area and monitoring at set time intervals, it can monitor the changes in charging demand in each area in real time, thereby improving the monitoring efficiency. It also enables the system to formulate charging equipment allocation and scheduling plans for different areas. During the monitoring time period, the number of search points in each monitoring area is obtained, and the peak and off-peak time periods of user demand are identified. According to the monitored peak and off-peak time periods, the charging equipment replenishment strategy is executed. During peak hours, the charging needs of users are met by replenishing charging equipment, reducing user waiting time and improving user experience.

[0016] 3. The intelligent management method for charging equipment defines a circular monitoring area with a radius of 3 kilometers with the charging station as the center point, covers the geographical range where users need charging services, integrates the location information of all charging stations and forms a set A, sets one week as a monitoring cycle and subdivides it into seven monitoring time periods, realizes the charging demand monitoring of the monitoring area within a week, sets a 2-hour monitoring time interval in each monitoring time period, divides 24 hours a day into 12 sub-monitoring time periods, collects charging demand data at a higher frequency, captures short-term fluctuations in demand, and analyzes charging demand in different time periods of a day, which helps the system identify the peak and low-peak charging periods of the day, so as to prepare for the corresponding peak period in the next monitoring cycle in advance, optimize the use efficiency of charging equipment, and rationally allocate resources during low-peak periods.

[0017] 4. The intelligent management method for charging equipment captures the dynamic demand of users for charging stations in real time by monitoring the search events of users on the charging equipment recommendation platform during the sub-monitoring time period. The search event is defined as the user searching for a nearby charging station on the charging equipment recommendation platform. Whenever a search event occurs in the monitoring area or a user uses the charging equipment in the monitoring area, the search points of the monitoring area are accumulated. Through this counting mechanism, the charging demand of users in each monitoring area is quantified. When entering the next sub-monitoring time period, the search points are reset and counted again, thereby realizing intermittent updating of the monitoring data.

[0018] 5. The intelligent management method of charging equipment obtains the search points of each sub-monitoring time period in the monitoring time cycle, analyzes the charging needs of users in different time periods, identifies the peak and off-peak time periods of user needs, marks the search points of the sub-monitoring time periods as peak values ​​in chronological order, and sorts them, selects the top three search points as the target peak search point set, and selects the top three search points as the target off-peak search point set, screens according to the number of charging devices in the monitoring area, identifies the peak time periods that require additional resource support, and the off-peak time periods with excess resources, marks the time period when the search points are greater than the number of charging devices as the peak time period, and marks the time period when the search points are less than the number of charging devices as the off-peak time period, dynamically adjusts the allocation of charging equipment according to real-time data, and reduces resource waste.

[0019] 6. The intelligent management method for charging equipment optimizes the allocation of charging equipment during peak time periods by implementing a charging equipment replenishment strategy, ensuring that users have enough charging equipment to charge in time during the highest demand periods, and determines whether other monitoring areas have low-peak time periods during this time period, and marks these areas as replenishment equipment areas accordingly, thereby realizing cross-regional resource allocation, improving the utilization efficiency of charging equipment, and reducing equipment idleness. After the peak time period ends, the replenished charging equipment is returned to the original area, ensuring the recycling and reasonable allocation of resources. When no monitoring area is in a low-peak time period during this time period, charging equipment is added at the beginning of the next monitoring cycle to meet the needs of the peak time period.

[0020] 7. The intelligent management method for charging equipment obtains the monitoring area containing the peak time period at the beginning of the monitoring cycle and forms a set, obtains the adjacent monitoring areas and forms a second monitoring area set, sets the peak time period monitoring time interval to 15 minutes, and collects user personal information data during each monitoring process. By comparing the number of search events in the monitoring area with the number of remaining charging devices, charging stations are recommended to meet user needs. When the number of search events exceeds the number of remaining charging devices, the user's location information is obtained and the distance to the charging station is calculated to form a sequence and sort it, which further optimizes the matching strategy of the charging station and ensures that the user is recommended to the nearest and most convenient charging station.

[0021] 8. The intelligent management method for charging equipment obtains the addresses and location information of the last three searches of users in the first user set, analyzes the users' charging needs and needs for going out, uses the users' search history and current location information to obtain routes, and provides users with charging station recommendations based on their actual driving paths. The location information in the second monitoring area set is considered to recommend suitable charging stations on the users' driving routes, thereby increasing the user's selection range. When a user selects a charging station in a monitoring area in the second monitoring area set, it is removed from the first user set. After removing the users who selected the second monitoring area, charging stations are recommended based on the number of remaining users in the first user set and the remaining number of charging devices in the first monitoring area set. Recommendations are made in the order of the users' distance from the charging stations from near to far, giving priority to satisfying the needs of users who are closer. For users whose corresponding elements in the first monitoring area set are not recommended, it is recommended to select charging stations in the second monitoring area set to ensure that all users can be served. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Embodiment 1, optionally, a charging station information unit, a charging device information unit and a user information unit are set; Recommend charging stations to users through the charging equipment recommendation platform; The charging station information unit is used to store the location information of the charging station and the number of charging devices in the charging station; The charging device information unit is used to collect the usage status of the charging device and the power of the charging device; The charging equipment usage status is divided into the to-be-allocated status and the allocated status; The user information unit is used to store the personal information data of the user when using the charging device recommendation platform; The personal information data includes, when a search event occurs, if the user agrees that the system will take the personal information data, the user's search time and the user's last three search addresses will be obtained; If the user does not agree that the system uses personal information data, the system will recommend the nearest charging equipment to the user based on the user's current geographical location; By constructing the charging station information unit, the charging equipment information unit and the user information unit, the management of the charging station location, the charging equipment status and the user's personal information is realized. According to the real-time information of the charging station and the specific needs of the user, the appropriate charging station is recommended for charging. Through the charging equipment recommendation platform, the user's search time, location information and historical search address are analyzed to provide users with personalized charging station recommendations. The charging equipment information unit collects the usage status and power information of the charging equipment, so that the system can adjust the allocation strategy of the charging equipment according to the pending allocation status and the allocated status of the equipment; Optionally, if the user searches for a nearby charging station through the charging device recommendation platform, this event is recorded as a search event; Obtain the locations of all charging stations, divide them into monitoring areas, and monitor the monitoring areas according to the monitoring time intervals; During the monitoring period, the number of search points in each monitoring area is obtained through the charging equipment recommendation platform; According to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located, obtain the peak time period and the off-peak time period of each monitoring area in the monitoring time cycle; Execute charging equipment replenishment strategy based on peak and off-peak time periods in all monitoring areas; The charging station matching strategy is implemented based on the personal information data collected by the charging equipment recommendation platform during the peak time periods of all monitoring areas.

[0025] Optionally, the acquiring the locations of all charging stations, dividing the monitoring areas, and monitoring the monitoring areas according to the monitoring time intervals includes: According to the location of the charging station, a circular area with a radius of 3 kilometers is delineated with the charging station as the center point, and the circular area is marked as the monitoring area; Get the locations of all charging stations and group the marked monitoring areas into a set, recorded as set A; Set monitoring time period; The monitoring cycle is set to one week, and each cycle is divided into seven monitoring time periods, namely Monday, Tuesday...Sunday; In each monitoring period, set the monitoring time interval, which is 2h; According to the monitoring time interval, the 24 hours of a day are divided into 12 sub-monitoring time periods, which are respectively recorded as the first time period, the second time period ... the twelfth time period.

[0026] Optionally, obtaining the number of search points in each monitoring area through the charging device recommendation platform during the monitoring time period includes: During the sub-monitoring time period, monitoring the user's search events on the charging device recommendation platform; The search event is that the user searches for nearby charging stations in the charging equipment recommendation platform; If a search event occurs in the monitoring area, the search points of the monitoring area are accumulated once, and the accumulated value is 1; If the user uses the charging equipment of a charging station once in the monitoring area, the search points of the monitoring area will be accumulated once, and the accumulated value is 1; When entering the next sub-monitoring time period, the search points in the monitoring area will be reset and counted again.

[0027] Optionally, obtaining the number of peak search points and the number of low peak search points in each monitoring time period in the monitoring time cycle according to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located, includes: Obtain the number of search points corresponding to each sub-monitoring time period in the monitoring time period; According to the temporal order of the sub-monitoring time periods, the search points of the sub-monitoring time periods are recorded as the first peak value, the second peak value, ... the twelfth peak value; Sort the first peak, the second peak, ... the twelfth peak in descending order according to the number of search points to form a sequence; Select the top three search points in the sequence to form a set, which is recorded as the target peak search point set; Select the last three search points in the sequence to form a set, which is recorded as the target low-peak search point set; Obtain the number of charging devices in the monitoring area, and filter the elements in the target peak search point set and the target low peak search point set respectively. The filtering steps are as follows: In the target peak search point set, if the search point number is greater than the number of charging devices in the monitoring area, the time period is marked as the peak time period of the monitoring area; In the target low-peak search point set, if the search point number is less than the number of charging devices in the monitoring area , then the time period is marked as the low-peak time period of the monitoring area.

[0028] By recording the user's search events, the user's charging needs are obtained in real time. By dividing the monitoring area and monitoring at the set time interval, the charging demand changes in each area can be monitored in real time, which improves the monitoring efficiency. It also enables the system to formulate charging equipment allocation and scheduling plans for different areas. During the monitoring period, the number of search points in each monitoring area is obtained, and the peak and off-peak time periods of user needs are identified. According to the monitored peak and off-peak time periods, the charging equipment replenishment strategy is implemented. During peak hours, the charging needs of users are met by replenishing charging equipment, reducing user waiting time and improving user experience. Optionally, executing a charging equipment replenishment strategy according to peak time periods and off-peak time periods of all monitoring areas includes: The charging equipment replenishment strategy is: S1: According to the peak time period of the monitoring area, determine whether the sub-monitoring time periods of other monitoring areas are marked as off-peak time periods; If a sub-monitoring time period of a monitoring area is marked as a low-peak time period, the monitoring area is marked as a supplementary equipment area; The charging equipment in the supplementary equipment area supplements the charging equipment in the monitoring area during the peak time period, and returns the supplemented charging equipment after the peak time period ends; S2: If the monitoring area is in the peak time period and no monitoring area is in the off-peak time period, then at the beginning of the next monitoring cycle, a charging device is added to the monitoring area; The number of newly added charging devices = the number of target peak search points - the number of charging devices in the monitoring area.

[0029] By implementing the charging equipment replenishment strategy, the allocation of charging equipment is optimized during peak hours to ensure that users have enough charging equipment to charge in time during the period with the highest demand. It is determined whether other monitoring areas have low-peak periods during this period, and these areas are marked as replenishment equipment areas accordingly, thus realizing cross-regional resource allocation, improving the efficiency of charging equipment use, and reducing equipment idleness. After the peak period, the replenished charging equipment is returned to the original area, ensuring the recycling and reasonable allocation of resources. When no monitoring area is in the low-peak period during this period, charging equipment is added at the beginning of the next monitoring cycle to meet the demand during the peak period. Optionally, executing a charging station matching strategy according to the personal information data collected by the charging equipment recommendation platform during the peak time period of all monitoring areas includes: At the beginning of the next monitoring cycle, all monitoring areas with peak time periods in the previous monitoring cycle are obtained and grouped to form a first monitoring area group; Acquire adjacent monitoring areas of each first monitoring area in the first monitoring area set, and form a second monitoring area set; Wherein the elements in the first monitoring region set correspond to certain elements in the second monitoring region set; According to the first monitoring area set, all monitoring areas in the set are monitored; The monitoring interval during peak hours is set to 15 minutes, and monitoring is performed every 15 minutes. During each monitoring process, the charging equipment recommendation platform collects the user's personal information data; By obtaining the monitoring area containing the peak time period at the beginning of the monitoring cycle and forming a set, obtaining the adjacent monitoring areas and forming a second monitoring area set, setting the peak time period monitoring time interval to 15 minutes, and collecting user personal information data during each monitoring process, by comparing the number of search events in the monitoring area with the number of remaining charging devices, recommending charging stations to meet user needs, when the number of search events exceeds the number of remaining charging devices, obtaining user location information and calculating the distance to the charging station, forming a sequence and sorting, further optimizing the matching strategy of the charging station, ensuring that users are recommended to the nearest and most convenient charging station; According to the personal information data, obtain the number of search events of the user in each monitoring area within the first monitoring area set, and the number of charging devices remaining in the monitoring area; If the number of search events in the monitoring area is less than the number of remaining charging devices in the monitoring area, the monitoring area is recommended to the user for charging; If the number of search events in the monitoring area is greater than the number of remaining charging devices in the monitoring area, the user who triggered the search event is obtained according to the personal information data to form a set, which is recorded as the first user set; According to the users in the first user set, the location information of all users is obtained, and the distance between the charging station and the user is calculated to form a sequence, and the sequence is sorted from small to large, and the sorted sequence is recorded as a first sequence; A charging station matching strategy is executed according to the first user set and the first sequence.

[0030] A circular monitoring area with a radius of 3 kilometers is defined with the charging station as the center point, covering the geographical range where users need charging services. The location information of all charging stations is integrated and formed into a set A. By setting one week as a monitoring cycle and subdividing it into seven monitoring time periods, the charging demand monitoring of the monitoring area within a week is realized. A 2-hour monitoring time interval is set in each monitoring time period, and 24 hours a day is divided into 12 sub-monitoring time periods. Charging demand data is collected at a higher frequency, short-term fluctuations in demand are captured, and charging demand at different time periods in a day is analyzed, which helps the system identify the peak and low-peak charging periods of the day, so as to prepare for the corresponding peak period in advance in the next monitoring cycle, optimize the use efficiency of charging equipment, and reasonably allocate resources during low-peak periods. Optionally, executing the charging station matching strategy according to the first user set and the first sequence includes: S3: Obtain the last three search addresses and location information of users in the first user set; S4: based on the last three search addresses and the user's location information, obtain a route between each search address and the user's current location; S5: Obtaining location information of elements in the second monitoring area set, and if the route passes through elements in the second monitoring area set, recommending the elements in the monitoring area and the first monitoring area set to the user; If the user selects a monitoring area in the second monitoring area set, the user is removed from the first user set and the first sequence; S6: If the number of elements in the first user set after elimination is greater than the number T of remaining charging devices of the corresponding elements in the first monitoring area set, then according to the first sequence after elimination, in order of the user's distance to the charging station in the first monitoring area, the corresponding elements in the first monitoring area set are recommended to the user for charging in sequence from near to far, until the remaining charging devices at the charging station are zero; S7: If there is a user in the first user set who is not recommended the corresponding element in the first monitoring area set, recommend the user to select the corresponding charging station in the second monitoring area set for charging.

[0031] Obtain the number of search points in each sub-monitoring time period in the monitoring time cycle, analyze the charging needs of users in different time periods, identify the peak and off-peak periods of user needs, mark the search points in the sub-monitoring time period as peak values ​​in chronological order, and sort them, select the top three search points in the sorting as the target peak search point set, and select the top three search points in the sorting as the target off-peak search point set, screen according to the number of charging devices in the monitoring area, identify the peak periods that require additional resource support, and the off-peak periods with excess resources, mark the time period when the number of search points is greater than the number of charging devices as the peak period, and mark the time period when the number of search points is less than the number of charging devices as the off-peak period, dynamically adjust the allocation of charging equipment according to real-time data, and reduce resource waste; It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0032] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A charging equipment intelligent management system, characterized in that: include: Setting a charging station information unit, a charging equipment information unit and a user information unit; Recommend charging stations to users through the charging equipment recommendation platform; The charging station information unit is used to store the location information of the charging station and the number of charging devices in the charging station; The charging device information unit is used to collect the usage status of the charging device and the power of the charging device; The charging equipment usage status is divided into the to-be-allocated status and the allocated status; The user information unit is used to store the personal information data of the user when using the charging device recommendation platform; The personal information data includes, when a search event occurs, obtaining the user's location information, the user's search time, and the user's last three search addresses.

2. A method for using a charging equipment intelligent management system, characterized in that: include: If the user searches for a nearby charging station through the charging device recommendation platform, this event is recorded as a search event; Obtain the locations of all charging stations, divide them into monitoring areas, and monitor the monitoring areas according to the monitoring time intervals; During the monitoring period, the number of search points in each monitoring area is obtained through the charging equipment recommendation platform; According to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located, obtain the peak time period and the off-peak time period of each monitoring area in the monitoring time cycle; Execute charging equipment replenishment strategy based on peak and off-peak time periods in all monitoring areas; The charging station matching strategy is implemented based on the personal information data collected by the charging equipment recommendation platform during the peak time periods of all monitoring areas.

3. The method for using the intelligent management system for charging equipment according to claim 2 is characterized by: The obtaining of the locations of all charging stations, dividing the monitoring areas, and monitoring the monitoring areas according to the monitoring time intervals includes: According to the location of the charging station, a circular area with a radius of 3 kilometers is delineated with the charging station as the center point, and the circular area is marked as the monitoring area; Get the locations of all charging stations and group the marked monitoring areas into a set, recorded as set A; Set monitoring time period; The monitoring cycle is set to one week, and each cycle is divided into seven monitoring time periods, namely Monday, Tuesday...Sunday; In each monitoring period, set the monitoring time interval, which is 2h; According to the monitoring time interval, the 24 hours of a day are divided into 12 sub-monitoring time periods, which are respectively recorded as the first time period, the second time period ... the twelfth time period.

4. The method for using the intelligent management system for charging equipment according to claim 2, characterized in that: During the monitoring period, the number of search points in each monitoring area is obtained through the charging equipment recommendation platform, including: During the sub-monitoring time period, monitoring the user's search events on the charging device recommendation platform; The search event is that the user searches for nearby charging stations in the charging equipment recommendation platform; If a search event occurs in the monitoring area, the search points of the monitoring area are accumulated once, and the accumulated value is 1; If the user uses the charging equipment of a charging station once in the monitoring area, the search points of the monitoring area will be accumulated once, and the accumulated value is 1; When entering the next sub-monitoring time period, the search points in the monitoring area will be reset and counted again.

5. The method for using the intelligent management system for charging equipment according to claim 2, characterized in that: The step of obtaining the number of high peak search points and the number of low peak search points in each monitoring time period in the monitoring time cycle according to each sub-monitoring time period and the monitoring time period in which the sub-monitoring time period is located comprises: Obtain the number of search points corresponding to each sub-monitoring time period in the monitoring time period; According to the temporal order of the sub-monitoring time periods, the search points of the sub-monitoring time periods are recorded as the first peak value, the second peak value, ... the twelfth peak value; Sort the first peak, the second peak, ... the twelfth peak in descending order according to the number of search points to form a sequence; Select the top three search points in the sequence to form a set, which is recorded as the target peak search point set; Select the last three search points in the sequence to form a set, which is recorded as the target low-peak search point set; Obtain the number of charging devices in the monitoring area, and filter the elements in the target peak search point set and the target low peak search point set respectively. The filtering steps are as follows: In the target peak search point set, if the search point number is greater than the number of charging devices in the monitoring area, the time period is marked as the peak time period of the monitoring area; In the target low-peak search point set, if the search point number is less than the number of charging devices in the monitoring area , then the time period is marked as the low-peak time period of the monitoring area.

6. The method for using the intelligent management system for charging equipment according to claim 2, characterized in that: The charging equipment replenishment strategy is executed according to the peak time periods and off-peak time periods of all monitoring areas, including: The charging equipment replenishment strategy is: S1: According to the peak time period of the monitoring area, determine whether the sub-monitoring time periods of other monitoring areas are marked as off-peak time periods; If a sub-monitoring time period of a monitoring area is marked as a low-peak time period, the monitoring area is marked as a supplementary equipment area; The charging equipment in the supplementary equipment area supplements the charging equipment in the monitoring area during the peak time period, and returns the supplemented charging equipment after the peak time period ends; S2: If the monitoring area is in the peak time period and no monitoring area is in the off-peak time period, then at the beginning of the next monitoring cycle, a charging device is added to the monitoring area; The number of newly added charging devices = the number of target peak search points - the number of charging devices in the monitoring area.

7. The method for using the intelligent management system for charging equipment according to claim 2, characterized in that: The charging station matching strategy is executed according to the personal information data collected by the charging equipment recommendation platform during the peak time period of all monitoring areas, including: At the beginning of the next monitoring cycle, all monitoring areas with peak time periods in the previous monitoring cycle are obtained and grouped to form a first monitoring area group; Acquire adjacent monitoring areas of each first monitoring area in the first monitoring area set, and form a second monitoring area set; Wherein the elements in the first monitoring region set correspond to certain elements in the second monitoring region set; According to the first monitoring area set, all monitoring areas in the set are monitored; The monitoring interval during peak hours is set to 15 minutes, and monitoring is performed every 15 minutes. During each monitoring process, the charging equipment recommendation platform collects the user's personal information data; According to the personal information data, obtain the number of search events of the user in each monitoring area within the first monitoring area set, and the number of charging devices remaining in the monitoring area; If the number of search events in the monitoring area is less than the number of remaining charging devices in the monitoring area, the monitoring area is recommended to the user for charging; If the number of search events in the monitoring area is greater than the number of remaining charging devices in the monitoring area, the user who triggered the search event is obtained according to the personal information data to form a set, which is recorded as the first user set; According to the users in the first user set, the location information of all users is obtained, and the distance between the charging station and the user is calculated to form a sequence, and the sequence is sorted from small to large, and the sorted sequence is recorded as a first sequence; A charging station matching strategy is executed according to the first user set and the first sequence.

8. The method for using the intelligent management system for charging equipment according to claim 7, characterized in that: The executing the charging station matching strategy according to the first user set and the first sequence includes: S3: Obtain the last three search addresses and location information of users in the first user set; S4: based on the last three search addresses and the user's location information, obtain a route between each search address and the user's current location; S5: Obtaining location information of elements in the second monitoring area set, and if the route passes through elements in the second monitoring area set, recommending the elements in the monitoring area and the first monitoring area set to the user; If the user selects a monitoring area in the second monitoring area set, the user is removed from the first user set and the first sequence; S6: If the number of elements in the first user set after elimination is greater than the number T of remaining charging devices of the corresponding elements in the first monitoring area set, then according to the first sequence after elimination, in order of the user's distance to the charging station in the first monitoring area, the corresponding elements in the first monitoring area set are recommended to the user for charging in sequence from near to far, until the remaining charging devices at the charging station are zero; S7: If there is a user in the first user set who is not recommended the corresponding element in the first monitoring area set, recommend the user to select the corresponding charging station in the second monitoring area set for charging.

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