Charging pile platform

Abstract

The invention discloses a charging pile platform, which comprises a multi-region power utilization load data acquisition module, a region power utilization peak period grading dynamic monitoring module, a multi-period region charging pile operation data association module, a charging pile intelligent execution control module, a charging pile user interaction prediction display module and a central processing server, according to a charging pile group power distribution structure, the system is divided into a plurality of independent monitoring areas, electrical loads of different areas in a community are sensed in real time, the real-time load state of each area is analyzed, intervention measures are actively taken before a transformer is overloaded, and the working modes of charging piles in the areas are intelligently determined. The operation states and rates of the charging piles in different areas are dynamically regulated and controlled, the situation that part of the charging piles are idle and part of the charging piles are overloaded is avoided, and space balance of charging resources and electric power resources in a community is achieved.

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-region real-time load rate time-segmented analysis submodule and a dynamic load threshold classification and prediction submodule. The multi-region real-time load rate time-segmented 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 periods by hours, and extracts any time within each hourly time period of the residential area to monitor the total active power, 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 P. tr Calculate the real-time load rate (LR) within several residential electricity monitoring areas during an hourly time period. The monitoring of residential electricity consumption is mapped to date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays. The load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays are set as p... cj 1 p cj 2 p cj 3 The monitoring date attribute is pre-labeled. The real-time load rate within 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 LR within several residential electricity monitoring areas within an hourly time period is ≥ p. cj 1 Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load factor LR ≥ p within several residential electricity monitoring areas within each hourly period is calculated. cj 2 Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate LR ≥ p within several residential electricity monitoring areas within the hourly period is considered. cj 3 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 to L. gt L gt >p cj 1 >p cj 2 >p cj 3 When the load factor during the peak electricity consumption period is LR, LR≤L gt If it is determined to be a single peak electricity consumption period, it will be removed from the peak electricity consumption periods aggregated within the residential electricity monitoring area on different dates. When LR > L gt 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, an early warning is issued through the central processing server, marking these periods as high-alert intervals. Continue to monitor its peak electricity consumption periods and compare them in real time with the preset safe warning load rate threshold;

[0019] Set the load rate threshold for peak electricity consumption periods as KL gt 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... The real-time load rate of the residential electricity monitoring area was determined to be at risk of overload during the high-alert period, and a warning mark was set. When the average real-time load rate during the high-alert period... Dynamically predict future electricity load rates during the current high-alert period. Collect data arbitrarily from three short time intervals within the high-alert period, with the length of each interval set manually. These short time intervals are designated as T. L1 T L1 T L2The median of the real-time load factor data for the residential electricity monitoring area within different short-term intervals is F. LR 1 F LR 2 F LR 3 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] Among them, λ% μ% is the load factor growth coefficient. 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 sum of the instantaneous power of all charging piles in a charging pile group that are currently charging is set as P. total The total active power during any peak electricity consumption period within the residential electricity monitoring area corresponding to the current charging pile group is arbitrarily collected, and the total active power P within the residential electricity monitoring area during the peak electricity consumption period is set. ft 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, monitors and 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. It obtains rate information for different charging pile groups, sets the current charging fee for the charging pile group to U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the warning mark period, the increased fee for charging piles currently charging within the currently adjustable charging pile group is (1+2φ)U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the critical warning period, the increased fee for charging piles within the currently adjustable charging pile group is (1+2φ)U. The fee increase for idle charging piles and charging piles that are charging is (1+φ)U. When the monitoring period of the current adjustable charging pile group is the warning mark period or the critical warning period period, the real-time load rate of the corresponding civil electricity monitoring area of ​​the charging pile group with low utilization is checked to determine whether it is the peak electricity consumption period. If not, the fee of the charging pile group with low utilization is reduced. The fee reduction rate of the charging pile group with low utilization is set to (1-φ)U, where φ is the adjustment coefficient, which 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-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, and divides the time periods by hours. It then extracts any time within each hourly time period of a residential area to monitor the total active power, 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 P. tr Calculate the real-time load rate (LR) within several residential electricity monitoring areas during an hourly time period. The monitoring of residential electricity consumption is mapped to date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays. The load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays are set as p... cj 1 p cj 2 p cj3 The monitoring date attribute is pre-labeled. The real-time load rate within 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 LR within several residential electricity monitoring areas within an hourly time period is ≥ p. cj 1 Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load factor LR ≥ p within several residential electricity monitoring areas within each hourly period is calculated. cj 2 Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate LR ≥ p within several residential electricity monitoring areas within the hourly period is considered. cj 3 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 to L. gt L gt >p cj 1 >p cj 2 >p cj 3 When the load factor during the peak electricity consumption period is LR, LR≤L gt If it is determined to be a single peak electricity consumption period, it will be removed from the peak electricity consumption periods aggregated within the residential electricity monitoring area on different dates. When LR > L gt 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, an early warning is issued through the central processing server, marking these periods as high-alert intervals. Continue to monitor its peak electricity consumption periods and compare them in real time with the preset safe warning load rate threshold;

[0044] Set the load rate threshold for peak electricity consumption periods as KL gt 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... The real-time load rate of the residential electricity monitoring area was determined to be at risk of overload during the high-alert period, and a warning mark was set. When the average real-time load rate during the high-alert period... Dynamically predict future electricity load rates during the current high-alert period. Collect data arbitrarily from three short time intervals within the high-alert period, with the length of each interval set manually. These short time intervals are designated as T. L1 T L1 T L2 The median of the real-time load factor data for the residential electricity monitoring area within different short-term intervals is F. LR 1 F LR 2 F LR 3 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] Among them, λ% μ% is the load factor growth coefficient. 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 sum of the instantaneous power of all charging piles in a charging pile group that are currently charging is set as P. total The total active power during any peak electricity consumption period within the residential electricity monitoring area corresponding to the current charging pile group is arbitrarily collected, and the total active power P within the residential electricity monitoring area during the peak electricity consumption period is set. ft 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, monitors and 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. It obtains rate information for different charging pile groups, sets the current charging fee for the charging pile group to U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the warning mark period, the increased fee for charging piles currently charging within the currently adjustable charging pile group is (1+2φ)U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the critical warning period, the increased fee for charging piles within the currently adjustable charging pile group is (1+2φ)U. The fee increase for idle charging piles and charging piles that are charging is (1+φ)U. When the monitoring period of the current adjustable charging pile group is the warning mark period or the critical warning period period, the real-time load rate of the corresponding civil electricity monitoring area of ​​the charging pile group with low utilization is checked to determine whether it is the peak electricity consumption period. If not, the fee of the charging pile group with low utilization is reduced. The fee reduction rate of the charging pile group with low utilization is set to (1-φ)U, where φ is the adjustment coefficient, which 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 pile platform, characterized in that: 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. 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. 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. 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. 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. 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. 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.

2. The charging pile platform according to claim 1, characterized in 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 a 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.

3. A 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-segmented analysis submodule and a dynamic load threshold classification and prediction submodule. The multi-region real-time load rate time-segmented 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 periods by hours, and extracts any time within each hourly time period to monitor the total active power. 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 P. tr Calculate the real-time load rate (LR) within several residential electricity monitoring areas during an hourly time period. The monitoring of residential electricity consumption is mapped to date attributes, including weekdays, weekends, and special holidays. The central processing server presets multiple load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays. The load factor thresholds for each residential electricity consumption monitoring area for weekdays, weekends, and special holidays are set as p... cj 1 p cj 2 p cj 3 The monitoring date attribute is pre-labeled. The real-time load rate within 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 LR within several residential electricity monitoring areas within an hourly time period is ≥ p. cj 1 Peak values ​​are marked for hourly periods. When the monitoring date is a weekend, the real-time load factor LR ≥ p within several residential electricity monitoring areas within each hourly period is calculated. cj 2 Peak values ​​are marked for hourly periods. When the monitoring date is a special holiday, the real-time load rate LR ≥ p within several residential electricity monitoring areas within the hourly period is considered. cj 3 Peak hours are marked for hourly periods to screen peak electricity consumption periods within the residential electricity monitoring area on different dates.

4. A charging pile platform according to claim 3, characterized in that... The dynamic load threshold classification 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 determines whether the time periods adjacent to the peak electricity consumption periods are also peak electricity consumption periods. 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 to L. gt L gt >p cj 1 >p cj 2 >p cj 3 When the load factor during the peak electricity consumption period is LR, LR≤L gt If it is determined to be a single peak electricity consumption period, it will be removed from the peak electricity consumption periods aggregated within the residential electricity monitoring area on different dates. When LR > L gt 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. 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, an early warning is issued through the central processing server, marking these periods as high-alert intervals. Continue to monitor its peak electricity consumption periods and compare them in real time with the preset safe warning load rate threshold; Set the load rate threshold for peak electricity consumption periods as KL gt 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... The real-time load rate of the residential electricity monitoring area was determined to be at risk of overload during the high-alert period, and a warning mark was set. When the average real-time load rate during the high-alert period... Dynamically predict future electricity load rates during the current high-alert period. Collect data arbitrarily from three short time intervals within the high-alert period, with the length of each interval set manually. These short time intervals are designated as T. L1 T L1 T L2 The median of the real-time load factor data for the residential electricity monitoring area within different short-term intervals is F. LR 1 F LR 2 F LR 3 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: Among them, λ% μ% is the load factor growth coefficient. 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.

5. A charging pile platform according to claim 1, characterized in 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. The 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. 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 sum of the instantaneous power of all charging piles in a charging pile group that are currently charging is set as P. total The total active power during any peak electricity consumption period within the residential electricity monitoring area corresponding to the current charging pile group is arbitrarily collected, and the total active power P within the residential electricity monitoring area during the peak electricity consumption period is set. ft 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.

6. A charging pile platform according to claim 1, characterized in 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 acquires the service status of individual charging piles within all marked adjustable charging pile groups, screens charging piles that are charging and idle charging piles, acquires 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, the critical warning interval, or the warning mark interval. 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. 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. 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.

7. A charging pile platform according to claim 6, characterized in that... 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. It obtains rate information for different charging pile groups, sets the current charging fee for the charging pile group to U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the warning mark period, the increased fee for charging piles currently charging within the adjustable charging pile group is (1+2φ)U. If the monitoring period of the residential electricity monitoring area corresponding to the adjustable charging pile group is within the critical warning period, the increased fee for charging piles within the adjustable charging pile group is (1+2φ)U. The increase in fees for idle charging piles and charging piles that are charging is (1+φ)U. When the monitoring period of the current adjustable charging pile group is the warning mark period or the critical warning period period, the real-time load rate of the corresponding civil electricity monitoring area of ​​the charging pile group with low utilization is screened to determine whether it is the peak electricity consumption period. If not, the fees of the charging pile group with low utilization are reduced. The reduction rate of the charging pile group with low utilization is set to (1-φ)U, where φ is the adjustment coefficient, which is set manually.

8. A charging pile platform according to claim 1, characterized in 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 power grid load status as normal, peak, or warning risk 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, critical-warning-range, 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. 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.

Images