A charging pile platform

Abstract

The application discloses a charging pile platform, which comprises a multi-region power consumption load data acquisition module, a regional power consumption peak period grading dynamic monitoring module, a multi-period regional charging pile operation data correlation module, a charging pile intelligent execution control module, a charging pile user interaction prediction display module and a central processing server, aims to be divided into multiple independent monitoring regions according to a charging pile group power distribution structure, to realize real-time sensing of power consumption loads in different regions in a cell, to analyze the real-time load state of each region, to take intervention measures before a transformer overload, to intelligently determine the working mode of the charging piles in the region, to dynamically regulate the operation state and the rate of the charging piles in different regions, to avoid the situation that some charging piles are idle and some charging piles are overloaded, and to realize spatial balance of charging resources and power resources in the cell.

Description

Technical Field

[0001] This invention relates to the field of smart charging, specifically a charging pile platform. Background Technology

[0002] With the increasing popularity of electric vehicles, the demand for charging stations in residential communities has increased dramatically. However, the power distribution capacity of residential communities is usually designed according to the daily electricity consumption of residents. The large number of newly added charging stations, especially fast charging stations, have huge power outputs and are very likely to create peak electricity consumption during certain periods, leading to local transformer overload, unstable grid voltage, and even safety accidents such as power outages.

[0003] Currently, existing solutions involve uniformly reducing the power of all charging stations when the total residential electricity load is high, but this affects the user experience and cannot solve the problem of regional imbalance. The second solution is simple time-of-use pricing, which sets a fixed charging price for a fixed period based on the peak and valley electricity prices of the municipal power grid. However, this cannot respond to real-time and dynamic load changes within the community, and all users are affected. It cannot meet the peak electricity demand of residents, and it cannot distinguish regional differences, which may result in excessive or insufficient restrictions. Charging stations in low-load areas are also restricted, resulting in idle resources.

[0004] This application aims to divide the charging pile group into multiple independent monitoring areas according to the power distribution structure, to sense the power load of different areas within the community in real time, to analyze the real-time load status of each area, to take proactive intervention measures before the transformer is overloaded, to intelligently determine the working mode of the charging piles in that area, and to dynamically regulate the operating status and tariff of the charging piles in different areas, thereby avoiding the situation where some charging piles are idle and others are overloaded, and achieving a spatial balance between charging resources and power resources within the community. Summary of the Invention

[0005] The purpose of this invention is to provide a charging pile platform to solve the problems in the prior art.

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

[0007] A charging pile platform includes a multi-regional electricity load data acquisition module, a regional peak-hour hierarchical dynamic monitoring module, a multi-time-hour regional charging pile operation data association module, a charging pile intelligent execution control module, a charging pile user interaction prediction and display module, and a central processing server. The multi-regional electricity load data acquisition module, the regional peak-hour hierarchical dynamic monitoring module, the multi-time-hour regional charging pile operation data association module, the charging pile intelligent execution control module, and the charging pile user interaction prediction and display module are interconnected and each is connected to the central processing server.

[0008] The multi-area power load data acquisition module collects power distribution areas corresponding to different charging pile locations, filters the power distribution areas as residential power consumption areas, and collects the overall power load data and historical load data of different charging pile locations within the community in real time within the set area range.

[0009] The regional peak-hour dynamic monitoring module analyzes the peak and off-peak hours of electricity consumption in different areas based on the electricity load data of different locations within the community, and further classifies the peak hours of electricity consumption in different charging pile locations.

[0010] The multi-time-period regional charging pile operation data association module uses smart meters to collect power data from charging piles, monitor the status of charging piles, and perform charging load analysis in conjunction with peak electricity consumption periods.

[0011] The intelligent execution control module of the charging pile dynamically adjusts the power load of the area where the charging pile is located during peak hours, and performs restrictive operations on the charging pile during peak power consumption periods within the area. The restrictive operations include suspending charging services or adjusting and analyzing the charging rate metering.

[0012] The charging pile user interaction prediction and display module is used to display and alarm the current power consumption status of different areas, as well as the availability status of charging piles and charging rates.

[0013] The central processing server is used to connect to the municipal power grid system, obtain grid-level time-of-use electricity price information, and connect to the power monitoring terminal to receive raw electricity usage data streams.

[0014] Further configuration: The multi-area electricity load data acquisition module includes a sub-module for locating charging pile distribution areas and a sub-module for statistically analyzing residential electricity load data. The sub-module for locating charging pile distribution areas collects the location of the charging piles to be monitored and marks the location areas of the charging pile distribution areas that are residential electricity consumption areas in the community. When the number of charging piles exceeds a set threshold, the residential electricity monitoring area is delineated according to the set location of the charging piles, with the currently monitored charging pile group as the center, and according to the set range. The set range is set by the administrator. Different residential electricity monitoring areas within the community are sent to the sub-module for statistically analyzing residential electricity load data. The sub-module for statistically analyzing residential electricity load data includes several smart meters. The smart meters monitor and collect the overall electricity load data of different residential electricity monitoring areas within the community, preprocess the data characteristics, and remove obvious abnormal values ​​caused by communication interference. Obvious abnormal values ​​include instantaneous huge spikes or zero values ​​in the power value. The power consumption data of different residential electricity monitoring areas at different times are summarized.

[0015] Further configuration: The regional peak-hour dynamic monitoring module includes a multi-regional real-time load rate time-segmentation analysis submodule and a dynamic load threshold classification and prediction submodule. The multi-regional real-time load rate time-segmentation analysis submodule acquires power consumption data for different time periods in different residential power monitoring areas, calculates the real-time load rate of the residential power monitoring areas for different time periods, divides the time period by hours, extracts the total active power at any time within each hourly time period of the community for monitoring, obtains the total active power values ​​of several residential power monitoring areas within each hourly time period, filters out the maximum and minimum values ​​of the total active power values, and calculates the average total active power of several residential power monitoring areas within each hourly time period. The rated power of the distribution transformer in this area is set as follows: Calculate the real-time load rate within several residential electricity monitoring areas within an hourly time period. , The system maps the monitoring areas for residential electricity consumption to specific date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each of these monitoring areas for weekdays, weekends, and special holidays. The specific load factor thresholds for each of these monitoring areas are set as follows: , , The monitoring date attribute is pre-labeled. The real-time load rate of several residential electricity monitoring areas within an hourly time period of the monitoring date is compared with the load rate thresholds set for different dates. When the monitoring date attribute is a weekday, the real-time load rate of several residential electricity monitoring areas within an hourly time period is... Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load rate within several residential electricity monitoring areas is recorded within each hourly period. Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate of several residential electricity monitoring areas within the hourly period is also recorded. Peak hours are marked for hourly periods to screen peak electricity consumption periods within the residential electricity monitoring area on different dates.

[0016] Further settings: The dynamic load threshold classification judgment and prediction submodule obtains and summarizes the peak electricity consumption periods within the monitoring area of ​​civil electricity on different dates, obtains the time periods adjacent to the peak electricity consumption periods, and judges whether the time periods adjacent to the peak electricity consumption periods are also peak electricity consumption periods;

[0017] If the period adjacent to the peak electricity consumption period is not a peak electricity consumption period, the load rate of that peak electricity consumption period is compared with the preset safe warning load rate threshold, and the preset safe warning threshold is set as follows. , During the peak electricity consumption period, the load factor , It is determined to be a single peak electricity consumption period, and this single peak electricity consumption period is removed from the peak electricity consumption periods aggregated within the residential electricity monitoring area on different dates. The system obtains and compares the load data of the peak electricity consumption period with the historical load data of the same period, and screens whether the frequency of the peak electricity consumption period data in the historical load data of the same period is greater than the set frequency. If the frequency of the peak electricity consumption period data is less than the set frequency, the peak electricity consumption period is determined to be a special peak electricity consumption period and is removed.

[0018] If consecutive peak electricity consumption periods are also peak electricity consumption periods, these consecutive peak electricity consumption periods are aggregated and marked as specific peak electricity consumption intervals, and the average real-time load factor of different peak electricity consumption intervals is obtained. The average real-time load factor of the residential electricity monitoring area during different peak electricity consumption periods is compared with the preset safe warning load factor threshold. If the system determines that the load is high during peak electricity consumption periods, it issues an early warning through the central processing server, marking these periods as high-alert intervals. We will continue to monitor the peak electricity consumption periods and compare them in real time with the preset safety warning load rate threshold.

[0019] Set the load rate threshold for early warning during peak electricity consumption periods as follows: The average real-time load factor of the residential electricity monitoring area during the high-alert period is compared with the warning load factor threshold during peak electricity consumption periods. When the average real-time load factor of the electricity consumption during the high-alert period is... If the real-time load rate of the residential electricity monitoring area is determined to be at risk of overload during the high-alert period, a warning mark is set. When the average real-time load rate of electricity during the high-alert period is... The system dynamically predicts future electricity load during the current high-alert period. It arbitrarily collects data from three short time intervals within the high-alert period, with the length of each interval set manually. The short time intervals are defined as follows: , , The median of real-time load factor data for residential electricity monitoring areas within different short-term intervals was obtained. , , The real-time load rate data of the residential electricity monitoring area within different short-term intervals were compared with the preset safety warning load rate threshold, according to the formula:

[0020]

[0021] in, , , This is the load factor growth rate. When all three short time intervals within a high-alert interval satisfy the above formula, the high-alert interval is marked as a critical warning interval. The high-alert interval, critical warning interval, and warning-marked interval for the civil electricity monitoring area within each historical monitoring date are summarized and uploaded to the central processing server.

[0022] Further configuration: The multi-time-period regional charging pile operation data association module includes a multi-region charging pile charging data aggregation sub-module and a regional charging pile load monitoring and analysis sub-module. The multi-region charging pile charging data aggregation sub-module includes the use of smart meters to collect the monitored charging pile group operation data, including individual charging pile status, daily charging times, output power, and tariff information. The individual charging pile status includes idle, faulty, and charging. The charging pile data is collected and uploaded, and charging piles with faults are reported to the central processing server for repair in real time.

[0023] The regional charging pile load monitoring and analysis submodule acquires individual charging pile data within each currently monitored charging pile group, and obtains the daily charging frequency for each charging pile group. If the daily charging frequency is less than a set threshold, the charging pile group is marked as having low utilization. If the daily charging frequency is greater than or equal to the set threshold, the instantaneous charging power of each charging pile in a charging pile group within that region that is currently charging is obtained. The total instantaneous power of all charging piles in a charging pile group that are currently charging is set as... The system can arbitrarily collect the total active power within the residential electricity monitoring area corresponding to the current charging pile group during any peak electricity consumption period, and set the total active power within the residential electricity monitoring area during peak electricity consumption periods. Calculate the charging load ratio of the current charging pile group in the residential electricity monitoring area. ,when If the value exceeds a set threshold, it is marked as an adjustable charging pile group, and statistics are performed on the groups marked as adjustable charging pile groups.

[0024] Further configuration: The intelligent execution control module for charging piles includes a dynamic adjustment submodule for charging pile services and a multi-level adjustment submodule for real-time charging rates. The dynamic adjustment submodule for charging pile services obtains the service status of individual charging piles within all marked adjustable charging pile groups, screens charging piles that are charging and idle charging piles respectively, obtains the real-time load rate of the civil electricity monitoring area corresponding to different adjustable charging pile groups, compares the real-time load rate of the corresponding civil electricity monitoring area with different load rate thresholds, and determines whether the current real-time monitoring interval of the civil electricity monitoring area belongs to the high-warning interval of electricity consumption, or the critical warning interval, or the warning mark interval.

[0025] When the real-time monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the warning mark period, the idle charging piles within the current adjustable charging pile group are shut down. At the same time, the charging pile clients that are charging are reminded of the increased billing. Meanwhile, the real-time load rate of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate is obtained within the current monitoring period. If the current monitoring period of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate is not the peak electricity consumption period, the location of the charging pile group marked with low utilization rate is marked and sent to the charging pile client for push notification, and the rate is reduced.

[0026] When the real-time monitoring interval of the civilian electricity monitoring area corresponding to the adjustable charging pile group is in the high warning interval, the charging pile client that is charging will be given a warning reminder of the current area power consumption.

[0027] When the real-time monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the critical warning period, the billing rate of currently idle charging piles is increased, and the billing rate of charging piles that are charging is alerted to be increased. The real-time load rate of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate within the current monitoring period is obtained. It is determined whether it is a peak electricity consumption period. The location of the charging pile group marked with low utilization rate is marked and sent to the charging pile client for push, and the rate is reduced.

[0028] Further settings: The multi-level adjustment submodule for real-time charging rates of charging piles is used to adjust the billing increase and decrease for different charging pile groups, obtain the rate information of different charging pile groups, and set the charging rate of the current charging pile group to [value missing]. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the warning mark period, the increased fee for charging piles currently charging within the adjustable charging pile group will be [amount missing]. If the monitoring period of the civilian electricity monitoring area corresponding to the adjustable charging pile group is within the critical warning period, the increase fee for idle charging piles and charging piles currently charging within the adjustable charging pile group will be: When the monitoring period of the residential electricity monitoring area corresponding to the currently adjustable charging pile group falls within the warning mark period or the critical warning mark period, and there are charging pile groups with low utilization rates, the real-time load rate of the corresponding residential electricity monitoring area is determined to determine whether it is a peak electricity consumption period. If not, the fees for the charging pile groups with low utilization rates are reduced. The reduction rate for charging pile groups with low utilization rates is set at a rate of [missing information]. ,in, The adjustment coefficient is set manually.

[0029] Further configuration: The charging pile user interaction prediction and display module includes a multi-region real-time power grid load display and feedback submodule and a multi-region charging rate prediction submodule. The multi-region real-time power grid load display and feedback submodule displays the real-time power grid load status of the residential power monitoring areas corresponding to different charging pile groups. It displays the normal power grid load status, peak power grid load status, and power grid load warning risk status for different residential power monitoring areas, respectively. It identifies whether the residential power monitoring areas corresponding to different charging pile groups are in high-warning-range periods, critical warning range periods, or warning-marked periods. Based on the identification results, it displays the information to users through the charging pile client, providing real-time display and push notifications of the charging pile status and charging prices for different charging pile groups.

[0030] Prioritize non-peak electricity consumption periods during different time periods, and send the location of charging pile groups marked with low usage rate to the charging pile client. At the same time, display and push the real-time charging price of charging pile groups marked with low usage rate in real time. The multi-region charging rate prediction submodule is used to mark the historical grid load status and high power consumption warning intervals, critical warning intervals, and warning mark periods in the civil power monitoring area corresponding to different charging pile groups. It predicts and pushes the same high power consumption warning interval, critical warning interval, and warning mark period, and predicts and pushes the charging rate of different charging piles during the same period.

[0031] Compared with the prior art, the beneficial effects of the present invention are: it aims to divide the charging pile group into multiple independent monitoring areas according to the power distribution structure, perceive the power load of different areas within the community in real time, analyze the real-time load status of each area, take proactive intervention measures before transformer overload, intelligently determine the working mode of the charging piles in the area, dynamically regulate the operating status and tariff of charging piles in different areas, avoid the situation of some charging piles being idle and some charging piles being overloaded, and achieve spatial balance between charging resources and power resources within the community. Attached Figure Description

[0032] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0033] Figure 1 This is a schematic diagram illustrating the connection of a specific system implementation of a charging pile platform according to the present invention;

[0034] Figure 2 This is a schematic diagram of the system structure of a charging pile platform according to the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Please see Figures 1-2 In this embodiment of the invention, a charging pile platform is provided. The platform includes a multi-regional electricity load data acquisition module, a regional peak electricity consumption period hierarchical dynamic monitoring module, a multi-time period regional charging pile operation data association module, a charging pile intelligent execution control module, a charging pile user interaction prediction and display module, and a central processing server. The multi-regional electricity load data acquisition module, the regional peak electricity consumption period hierarchical dynamic monitoring module, the multi-time period regional charging pile operation data association module, the charging pile intelligent execution control module, and the charging pile user interaction prediction and display module are interconnected and each is connected to the central processing server.

[0037] The multi-area power load data acquisition module collects power distribution areas corresponding to different charging pile locations, filters the power distribution areas as residential power consumption areas, and collects the overall power load data and historical load data of different charging pile locations within the community in real time within the set area range.

[0038] It should also be explained in more detail that the multi-area electricity load data acquisition module includes a sub-module for locating charging pile distribution areas and a sub-module for statistically analyzing residential electricity load data. The sub-module for locating charging pile distribution areas collects the location of the charging piles to be monitored and marks the location areas of the charging pile distribution areas that are residential electricity consumption areas in the community. When the number of charging piles exceeds a set threshold, the residential electricity monitoring area is delineated according to the set location of the charging piles, with the currently monitored charging pile group as the center, and according to the set range. The set range is set by the administrator. The different residential electricity monitoring areas within the community are sent to the sub-module for statistically analyzing residential electricity load data. The sub-module for statistically analyzing residential electricity load data includes several smart meters. The smart meters monitor and collect the overall electricity load data of different residential electricity monitoring areas within the community, preprocess the data characteristics, and remove obvious abnormal values ​​caused by communication interference. Obvious abnormal values ​​include instantaneous huge spikes or zero values ​​in the power value. The power consumption data of different residential electricity monitoring areas at different times are summarized.

[0039] The regional peak-hour dynamic monitoring module analyzes the peak and off-peak hours of electricity consumption in different areas based on the electricity load data of different locations within the community, and further classifies the peak hours of electricity consumption in different charging pile locations.

[0040] To further explain, the regional peak-hour dynamic monitoring module includes a multi-regional real-time load rate time-segmentation analysis submodule and a dynamic load threshold classification and prediction submodule. The multi-regional real-time load rate time-segmentation analysis submodule acquires power consumption data for different time periods in different residential power monitoring areas, calculates the real-time load rate of the residential power monitoring areas for different time periods, divides the time period by hours, and extracts the total active power for any time within each hourly time period of the residential area for monitoring. It obtains the total active power values ​​for several residential power monitoring areas within each hourly time period, filters out the maximum and minimum values ​​within these values, and calculates the average total active power for several residential power monitoring areas within each hourly time period. The rated power of the distribution transformer in this area is set as follows: Calculate the real-time load rate within several residential electricity monitoring areas within an hourly time period. , The system maps the monitoring areas for residential electricity consumption to specific date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each of these monitoring areas for weekdays, weekends, and special holidays. The specific load factor thresholds for each of these monitoring areas are set as follows: , , The monitoring date attribute is pre-labeled. The real-time load rate of several residential electricity monitoring areas within an hourly time period of the monitoring date is compared with the load rate thresholds set for different dates. When the monitoring date attribute is a weekday, the real-time load rate of several residential electricity monitoring areas within an hourly time period is... Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load rate within several residential electricity monitoring areas is recorded within each hourly period. Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate of several residential electricity monitoring areas within the hourly period is also recorded. Peak hours are marked for hourly periods to screen peak electricity consumption periods within the residential electricity monitoring area on different dates.

[0041] Further explanation is needed: the dynamic load threshold classification and prediction submodule collects and summarizes the peak electricity consumption periods within the residential electricity monitoring area on different dates, obtains the time periods adjacent to the peak electricity consumption periods, and determines whether the time periods adjacent to the peak electricity consumption periods are also peak electricity consumption periods.

[0042] If the period adjacent to the peak electricity consumption period is not a peak electricity consumption period, the load rate of that peak electricity consumption period is compared with the preset safe warning load rate threshold, and the preset safe warning threshold is set as follows. , During the peak electricity consumption period, the load factor , It is determined to be a single peak electricity consumption period, and this single peak electricity consumption period is removed from the peak electricity consumption periods aggregated within the residential electricity monitoring area on different dates. The system obtains and compares the load data of the peak electricity consumption period with the historical load data of the same period, and screens whether the frequency of the peak electricity consumption period data in the historical load data of the same period is greater than the set frequency. If the frequency of the peak electricity consumption period data is less than the set frequency, the peak electricity consumption period is determined to be a special peak electricity consumption period and is removed.

[0043] If consecutive peak electricity consumption periods are also peak electricity consumption periods, these consecutive peak electricity consumption periods are aggregated and marked as specific peak electricity consumption intervals, and the average real-time load factor of different peak electricity consumption intervals is obtained. The average real-time load factor of the residential electricity monitoring area during different peak electricity consumption periods is compared with the preset safe warning load factor threshold. If the system determines that the load is high during peak electricity consumption periods, it issues an early warning through the central processing server, marking these periods as high-alert intervals. We will continue to monitor the peak electricity consumption periods and compare them in real time with the preset safety warning load rate threshold.

[0044] Set the load rate threshold for early warning during peak electricity consumption periods as follows: The average real-time load factor of the residential electricity monitoring area during the high-alert period is compared with the warning load factor threshold during peak electricity consumption periods. When the average real-time load factor of the electricity consumption during the high-alert period is... If the real-time load rate of the residential electricity monitoring area is determined to be at risk of overload during the high-alert period, a warning mark is set. When the average real-time load rate of electricity during the high-alert period is... The system dynamically predicts future electricity load during the current high-alert period. It arbitrarily collects data from three short time intervals within the high-alert period, with the length of each interval set manually. The short time intervals are defined as follows: , , The median of real-time load factor data for residential electricity monitoring areas within different short-term intervals was obtained. , , The real-time load rate data of the residential electricity monitoring area within different short-term intervals were compared with the preset safety warning load rate threshold, according to the formula:

[0045]

[0046] in, , , This is the load factor growth rate. When all three short time intervals within a high-alert interval satisfy the above formula, the high-alert interval is marked as a critical warning interval. The high-alert interval, critical warning interval, and warning-marked interval for the civil electricity monitoring area within each historical monitoring date are summarized and uploaded to the central processing server.

[0047] The multi-time-period regional charging pile operation data association module uses smart meters to collect power data from charging piles, monitor the status of charging piles, and perform charging load analysis in conjunction with peak electricity consumption periods.

[0048] It should be further explained that the multi-time-period regional charging pile operation data association module includes a multi-region charging pile charging data aggregation sub-module and a regional charging pile load monitoring and analysis sub-module. The multi-region charging pile charging data aggregation sub-module includes collecting the monitored charging pile group operation data using smart meters, including individual charging pile status, daily charging times, output power, and tariff information. Individual charging pile status includes idle, faulty, and charging. The module collects and uploads charging pile data and reports faulty charging piles to the central processing server for repair in real time.

[0049] The regional charging pile load monitoring and analysis submodule acquires individual charging pile data within each currently monitored charging pile group, and obtains the daily charging frequency for each charging pile group. If the daily charging frequency is less than a set threshold, the charging pile group is marked as having low utilization. If the daily charging frequency is greater than or equal to the set threshold, the instantaneous charging power of each charging pile in a charging pile group within that region that is currently charging is obtained. The total instantaneous power of all charging piles in a charging pile group that are currently charging is set as... The system can arbitrarily collect the total active power within the residential electricity monitoring area corresponding to the current charging pile group during any peak electricity consumption period, and set the total active power within the residential electricity monitoring area during peak electricity consumption periods. Calculate the charging load ratio of the current charging pile group in the residential electricity monitoring area. ,when If the value exceeds a set threshold, it is marked as an adjustable charging pile group, and statistics are performed on the groups marked as adjustable charging pile groups.

[0050] The intelligent execution control module of the charging pile dynamically adjusts the power load of the area where the charging pile is located during peak hours, and performs restrictive operations on the charging pile during peak power consumption periods within the area. The restrictive operations include suspending charging services or adjusting and analyzing the charging rate metering.

[0051] It should be further explained that the intelligent execution control module for charging piles includes a dynamic adjustment submodule for charging pile services and a multi-level adjustment submodule for real-time charging rates. The dynamic adjustment submodule for charging pile services obtains the service status of individual charging piles within all marked adjustable charging pile groups, screens charging piles that are charging and idle charging piles respectively, obtains the real-time load rate of the civil electricity monitoring area corresponding to different adjustable charging pile groups, compares the real-time load rate of the corresponding civil electricity monitoring area with different load rate thresholds, and determines whether the current real-time monitoring interval of the civil electricity monitoring area belongs to the high-warning interval of electricity consumption, or the critical warning interval, or the warning mark interval.

[0052] When the real-time monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the warning mark period, the idle charging piles within the current adjustable charging pile group are shut down. At the same time, the charging pile clients that are charging are reminded of the increased billing. Meanwhile, the real-time load rate of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate is obtained within the current monitoring period. If the current monitoring period of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate is not the peak electricity consumption period, the location of the charging pile group marked with low utilization rate is marked and sent to the charging pile client for push notification, and the rate is reduced.

[0053] When the real-time monitoring interval of the civilian electricity monitoring area corresponding to the adjustable charging pile group is in the high warning interval, the charging pile client that is charging will be given a warning reminder of the current area power consumption.

[0054] When the real-time monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the critical warning period, the billing rate of currently idle charging piles is increased, and the billing rate of charging piles that are charging is alerted to be increased. The real-time load rate of the residential electricity monitoring area corresponding to the charging pile group marked with low utilization rate within the current monitoring period is obtained. It is determined whether it is a peak electricity consumption period. The location of the charging pile group marked with low utilization rate is marked and sent to the charging pile client for push, and the rate is reduced.

[0055] Further settings: The multi-level adjustment submodule for real-time charging rates of charging piles is used to adjust the billing increase and decrease for different charging pile groups, obtain the rate information of different charging pile groups, and set the charging rate of the current charging pile group to [value missing]. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group falls within the warning mark period, the increased fee for charging piles currently charging within the adjustable charging pile group will be [amount missing]. If the monitoring period of the civilian electricity monitoring area corresponding to the adjustable charging pile group is within the critical warning period, the increase fee for idle charging piles and charging piles currently charging within the adjustable charging pile group will be: When the monitoring period of the residential electricity monitoring area corresponding to the currently adjustable charging pile group falls within the warning mark period or the critical warning mark period, and there are charging pile groups with low utilization rates, the real-time load rate of the corresponding residential electricity monitoring area is determined to determine whether it is a peak electricity consumption period. If not, the fees for the charging pile groups with low utilization rates are reduced. The reduction rate for charging pile groups with low utilization rates is set at a rate of [missing information]. ,in, The adjustment coefficient is set manually.

[0056] The charging pile user interaction prediction and display module is used to display and alarm the current power consumption status of different areas, as well as the availability status of charging piles and charging rates.

[0057] It should be further explained that the charging pile user interaction prediction and display module includes a multi-region real-time power grid load display and feedback submodule and a multi-region charging rate prediction submodule. The multi-region real-time power grid load display and feedback submodule displays the real-time power grid load status of the residential power monitoring areas corresponding to different charging pile groups. It displays the normal power grid load status, peak power grid load status, and power grid load warning risk status for different residential power monitoring areas. It identifies whether the residential power monitoring areas corresponding to different charging pile groups are in the high power consumption warning interval, critical warning interval, or warning mark period. Based on the identification results, it displays the information to users through the charging pile client, and displays and pushes the charging pile status and charging price of different charging pile groups in real time.

[0058] Prioritize non-peak electricity consumption periods during different time periods, and send the location of charging pile groups marked with low usage rate to the charging pile client. At the same time, display and push the real-time charging price of charging pile groups marked with low usage rate in real time. The multi-region charging rate prediction submodule is used to mark the historical grid load status and high power consumption warning intervals, critical warning intervals, and warning mark periods in the civil power monitoring area corresponding to different charging pile groups. It predicts and pushes the same high power consumption warning interval, critical warning interval, and warning mark period, and predicts and pushes the charging rate of different charging piles during the same period.

[0059] The central processing server is used to connect to the municipal power grid system, obtain grid-level time-of-use electricity price information, and connect to the power monitoring terminal to receive raw electricity usage data streams.

[0060] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A charging post platform, characterized in that: The platform comprises a multi-region power consumption load data acquisition module, a regional power consumption peak period grading dynamic monitoring module, a multi-period regional charging pile operation data correlation module, a charging pile intelligent execution control module, a charging pile user interaction prediction display module and a central processing server, the multi-region power consumption load data acquisition module, the regional power consumption peak period grading dynamic monitoring module, the multi-period regional charging pile operation data correlation module, the charging pile intelligent execution control module and the charging pile user interaction prediction display module are connected with each other and are connected with the central processing server respectively; The multi-region power consumption load data acquisition module acquires the power distribution regions corresponding to different charging pile positions, filters the power distribution regions as residential power consumption regions, and acquires the overall power consumption load data and historical load data of different charging pile setting positions in the set region range in real time; The regional power consumption peak period grading dynamic monitoring module analyzes the power consumption peak period and the low peak period of different regions according to the power consumption load data of different positions in the community, and refines the power consumption peak period of different charging pile setting regions; The multi-period regional charging pile operation data correlation module uses the smart meter to acquire the power data of the charging pile, monitors the state of the charging pile, and analyzes the charging load in the power consumption peak period; The charging pile intelligent execution control module dynamically regulates the power load of the position region of the charging pile in the peak period, executes the restrictive operation on the charging pile in the peak power consumption period in the region, and the restrictive operation includes suspending the charging service or adjusting and analyzing the charging rate metering; The charging pile user interaction prediction display module is used for displaying and alarming the current power consumption state of different regions, and displaying the available state of the charging pile and the charging rate; The central processing server is used for connecting the municipal power grid system, acquiring the time-of-use electricity price information of the power grid level, and connecting the power monitoring terminal to receive the original power usage data stream.

2. The charging pile platform according to claim 1, characterized in that The multi-region power consumption load data acquisition module comprises a regional charging pile power distribution region positioning submodule and a residential power consumption region power consumption load data statistics submodule. The regional charging pile power distribution region positioning submodule acquires the positioning position of the charging pile to be monitored, marks the position region of the charging pile power distribution region as the residential power consumption region of the community, and when the number of charging piles is greater than a set threshold, the residential power consumption monitoring region is divided according to the set range with the current monitored charging pile group as the center, wherein the set range is set by the administrator. The different residential power consumption monitoring regions in the community are sent to the residential power consumption region power consumption load data statistics submodule. The residential power consumption region power consumption load data statistics submodule comprises a plurality of smart meters. The smart meters monitor and acquire the overall power consumption load data of different residential power consumption monitoring regions in the community, pre-process the data characteristics, eliminate obvious outliers caused by communication interference, and summarize the power consumption data of different residential power consumption monitoring regions at different periods.

3. The charging pile platform according to claim 1, characterized in that The regional peak-hour dynamic monitoring module includes a multi-region real-time load rate time-segmentation analysis submodule and a dynamic load threshold classification and prediction submodule. The multi-region real-time load rate time-segmentation analysis submodule acquires power consumption data for different time periods in different residential power monitoring areas, calculates the real-time load rate of the residential power monitoring areas for different time periods, divides the time period by hours, and extracts the total active power at any time within each hourly time period for monitoring. It obtains the total active power values ​​for several residential power monitoring areas within each hourly time period, filters out the maximum and minimum values ​​within these values, and calculates the average total active power for several residential power monitoring areas within each hourly time period. The rated power of the distribution transformer in this area is set as follows: Calculate the real-time load rate within several residential electricity monitoring areas within an hourly time period. , The system maps the monitoring areas for residential electricity consumption to specific date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each of these monitoring areas for weekdays, weekends, and special holidays. The specific load factor thresholds for each of these monitoring areas are set as follows: , , The monitoring date attribute is pre-labeled. The real-time load rate of several residential electricity monitoring areas within an hourly time period of the monitoring date is compared with the load rate thresholds set for different dates. When the monitoring date attribute is a weekday, the real-time load rate of several residential electricity monitoring areas within an hourly time period is... Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load rate within several residential electricity monitoring areas is recorded within each hourly period. Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate of several residential electricity monitoring areas within the hourly period is also recorded. Peak hours are marked for hourly periods to screen peak electricity consumption periods within the residential electricity monitoring area on different dates.

4. The charging pile platform according to claim 3, characterized in that The dynamic load threshold grading judgment prediction submodule obtains the use peak period inside the monitored different date civil electricity monitoring area, and performs collection, obtains adjacent time periods of the use peak period, and judges whether the adjacent time periods of the use peak period are also use peak periods; If the adjacent time period of the power consumption peak period is not a power consumption peak period, the load rate of the power consumption peak period is compared with the preset safety warning load rate threshold, and the preset safety warning threshold is set as , , when the load rate of the power consumption peak period is greater than the preset safety warning threshold, it is determined that the power consumption peak period is a single power consumption peak period, and the single power consumption peak period is excluded from the power consumption peak periods in the civil power monitoring area on different dates. When , , it is determined that the power consumption peak period is a single power consumption peak period, and the single power consumption peak period is excluded from the power consumption peak periods in the civil power monitoring area on different dates. When , the load data of the same period of the power consumption peak period is obtained for comparison, and it is screened whether the data frequency of the power consumption peak period is greater than the set frequency times. When the data frequency of the power consumption peak period is less than the set frequency times, it is determined that the power consumption peak period is a special power consumption peak period and is excluded. If the time period adjacent to the power consumption peak period is a power consumption peak period, the continuous power consumption peak period is marked as a specific power consumption peak interval period, and the real-time load rate average of different power consumption peak interval periods is obtained The real-time load rate average of the civil power monitoring area in different power consumption peak interval periods is compared with the preset safety warning load rate threshold, If the load of the power consumption peak interval period is high, the central processing server issues a warning and marks it as a high warning interval period, The power consumption peak interval period is continuously monitored and compared with the preset safety warning load rate threshold in real time. The warning load rate threshold value of the high peak period is set as The real-time load rate of the high warning interval period is compared with the warning load rate threshold value of the high peak period. When the real-time load rate of the high warning interval period is greater than the warning load rate threshold value of the high peak period, it is determined that the real-time load rate of the high warning interval period is in an overload risk, and a warning mark is given. The real-time load rate of the high warning interval period is compared with the warning load rate threshold value of the high peak period. When the real-time load rate of the high warning interval period is less than the warning load rate threshold value of the high peak period, it is determined that the real-time load rate of the high warning interval period is in an overload risk, and a warning mark is given. The future load rate of the current high warning interval period is dynamically predicted. Three short interval periods are randomly collected in time sequence in the high warning interval period. The length of the short interval period is set by a person. The short interval periods are set as 、 、 The median of the real-time load rate data of the domestic electricity monitoring area in different short interval periods is obtained as 、 、 The real-time load rate data of the domestic electricity monitoring area in different short interval periods are compared with the preset safety warning load rate threshold value. According to the formula: wherein, , , is a load rate growth coefficient, When the three short time interval sections within the high early warning interval section meet the above formula, mark the high early warning interval section as a critical alert interval section. Sum up the high early warning interval section, the critical alert interval section, and the alert marked section of the power consumption monitoring area in each historical monitoring date, and upload them to the central processing server.

5. The charging pile platform according to claim 1, characterized in that The multi-period area charging pile operation data correlation module includes a multi-area charging pile charging data collection submodule and a sub-area charging pile load monitoring analysis submodule. The multi-area charging pile charging data collection submodule includes collecting the charging pile group operation data monitored by the intelligent electric meter, including individual charging pile state, daily charging times, output power, and rate information. The individual charging pile state includes idle, fault, and charging. The charging pile data is collected and uploaded, and the charging pile with faults is reported to the central processing server in real time for maintenance. The sub-module for monitoring and analyzing the load of charging piles in different areas acquires individual data of charging piles in each charging pile group currently monitored, acquires daily charging times of each charging pile group, marks the charging pile group as low usage when the daily charging times are less than a set threshold, acquires instantaneous charging power of each charging pile in a charging state in the charging pile group when the daily charging times are greater than or equal to the set threshold, sets the sum of instantaneous powers of all charging piles in a charging state in a certain charging pile group as , acquires total active power of the domestic electricity monitoring area corresponding to the current charging pile group at any power consumption peak period, sets the total active power of the domestic electricity monitoring area at the power consumption peak period as , calculates the charging load ratio of the charging pile in the current charging pile group in the domestic electricity monitoring area as , marks the charging pile group as controllable when is greater than a set threshold, and performs statistics on the charging pile group marked as controllable.

6. The charging pile platform according to claim 5, characterized in that The charging pile intelligent execution control module includes a charging pile service dynamic regulation submodule and a charging pile real-time charging rate multi-level adjustment submodule. The charging pile service dynamic regulation submodule obtains the individual charging pile service state inside all marked controllable charging pile groups, respectively screens the charging pile in charging and the idle charging pile, obtains the real-time load rate of the corresponding civil electricity monitoring area of different controllable charging pile groups in real time, compares the real-time load rate of the corresponding civil electricity monitoring area with different load rate thresholds, and judges whether the current civil electricity monitoring area real-time monitoring interval period belongs to the electricity high warning interval period, or the critical warning interval period, or the warning mark period. When the real-time monitoring interval period of the controllable charging pile group corresponding civil electricity monitoring area belongs to the warning mark period, the idle charging pile inside the current controllable charging pile group is closed, the charging pile client in charging is charged and reminded to be adjusted up, the real-time load rate of the charging pile group corresponding civil electricity monitoring area with low usage rate in the current monitoring interval period is obtained, and if the current monitoring period of the charging pile group corresponding civil electricity monitoring area with low usage rate is not in the electricity peak interval, the position of the charging pile group with low usage rate is marked and sent to the charging pile client for rate adjustment. When the real-time monitoring interval period of the controllable charging pile group corresponding civil electricity monitoring area belongs to the high warning interval period, the charging pile client in charging is reminded of the current area power warning; When the real-time monitoring interval period of the controllable charging pile group corresponding civil electricity monitoring area belongs to the critical warning interval period, the idle charging pile is charged and reminded to be adjusted up, and the charging pile client in charging is charged and reminded to be adjusted up, the real-time load rate of the charging pile group corresponding civil electricity monitoring area with low usage rate in the current monitoring interval period is obtained, and whether it is in the electricity peak interval is judged, the position of the charging pile group with low usage rate is marked and sent to the charging pile client for rate adjustment.

7. The charging pile platform according to claim 6, characterized in that The real-time charging rate multi-stage adjustment submodule of the charging pile is used for adjusting the charging up and down of different charging pile groups, obtaining the rate information of different charging pile groups, setting the current charging pile group charging fee as , if the monitoring interval period of the civil electricity monitoring area corresponding to the controllable charging pile group is in the warning mark period, the upcharge of the charging pile in the current controllable charging pile group is , if the monitoring interval period of the civil electricity monitoring area corresponding to the controllable charging pile group is in the critical warning interval period, the upcharge of the idle charging pile and the charging pile in the current controllable charging pile group is , when the monitoring interval period of the civil electricity monitoring area corresponding to the current controllable charging pile group is the warning mark period or the critical warning interval period, the real-time load rate of the charging pile group corresponding to the civil electricity monitoring area with the low usage rate mark is screened, whether it is in the electricity peak interval is judged, if not, the charging pile group with the low usage rate mark is downcharged, and the downcharge rate of the charging pile group with the low usage rate mark is set as , wherein is an adjustment coefficient, which is set by human.

8. The charging pile platform according to claim 1, characterized in that The charging pile user interaction prediction display module comprises a multi-region real-time power grid load display feedback submodule and a multi-region charging rate prediction submodule. The multi-region real-time power grid load display feedback submodule displays the real-time power grid load state of different charging pile groups corresponding to the civil electricity monitoring area. The real-time power grid load state of different civil electricity monitoring areas is displayed as a normal power grid load state, a power grid load peak state and a power grid load early warning risk state. Whether the civil electricity monitoring area corresponding to the different charging pile groups is in the electricity high early warning interval period, the critical warning interval period and the warning mark period is identified. According to the identification result, the charging pile client is used to display and push the charging pile state and the charging price of different charging pile groups to the user in real time, The charging pile client is used to push the charging pile group position with the low usage rate mark to the user in real time, and the real-time charging price of the charging pile group with the low usage rate mark is displayed and pushed in real time. The multi-region charging rate prediction submodule is used to mark the historical power grid load state of different pile groups corresponding to the civil electricity monitoring area and the electricity high early warning interval period, the critical warning interval period and the warning mark period. The same electricity high early warning interval period, the critical warning interval period and the warning mark period are predicted and marked and pushed. Meanwhile, the charging rate of different charging piles in the period is predicted and pushed.

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