Charging station management method and system based on intelligent box

Abstract

The invention relates to a charging station management method and system based on an intelligent box, and relates to the field of the vehicle charging technology, and the method comprises the steps: obtaining the overall power of a power grid and the charging demand power of each current charging pile; determining the overall required power according to each charging required power, and determining the available power of the power grid according to the overall power of the power grid and the anti-disturbance coefficient; when the overall demand power is greater than the available power of the power grid, acquiring the battery capacity percentage, the residual charging duration and the vehicle priority coefficient of each vehicle according to each charging pile; calculating according to the battery capacity percentage, the residual charging duration and the vehicle priority coefficient to determine a vehicle basic weight; and calculating according to the available power of the power grid, the basic weight of the vehicle and the charging demand power to determine effective distribution power, and controlling each charging pile to operate at the corresponding effective distribution power. The method and the device have the effect of improving the charging experience when the vehicle is charged by using the charging station.

Description

Technical Field

[0001] The present application relates to the field of vehicle charging technologies, and particularly to a charging station management method and system based on an intelligent box. Background Art

[0002] With the rapid popularization of electric vehicles, the construction scale of charging stations has been continuously expanding. The traditional charging pile management method has been difficult to meet the efficient and intelligent charging requirements. To improve the operation efficiency of charging stations and the stability of the power grid, in the prior art, there has emerged a charging station management system based on an intelligent box, which realizes remote monitoring and load scheduling of charging piles through Internet of Things technology.

[0003] In the related art, through the intelligent box, the power distribution can be dynamically adjusted according to the grid capacity and the operating status of the charging piles. For example, when 10 fast charging piles of 120 kW work simultaneously, the total demand reaches 1200 kW, but the grid only supports 800 kW. At this time, through the intelligent box, the output power of each charging pile can be dynamically adjusted from 120 kW to 80 kW to reduce overload when multiple piles are charging.

[0004] In the above related art, in the process of power scheduling and distribution, the commonly used strategy at present is still simple average distribution, that is, the available power is evenly divided among all vehicles that are charging. Although the charging operation of the vehicles can be realized, the charging demands of each vehicle are different, resulting in a poor charging experience when the vehicle uses the current charging station for charging, and there is still room for improvement. Summary of the Invention

[0005] In order to improve the charging experience when a vehicle uses a charging station for charging, the present application provides a charging station management method and system based on an intelligent box.

[0006] In a first aspect, the present application provides a charging station management method based on an intelligent box, adopting the following technical solutions:

[0007] A charging station management method based on an intelligent box, comprising:

[0008] Obtain the overall power of the power grid and the charging demand power of each current charging pile;

[0009] Calculate according to each charging demand power to determine the overall demand power, and calculate according to the overall power of the power grid and a preset anti-disturbance coefficient to determine the available power of the power grid;

[0010] Judge whether the overall demand power is greater than the available power of the power grid;

[0011] If the overall demand power is not greater than the available power of the power grid, control each charging pile to operate at the corresponding charging demand power;

[0012] If the overall required power is greater than the available power of the power grid, then obtain the battery charge percentage, remaining charging duration, and vehicle priority coefficient of each vehicle according to each charging pile;

[0013] Perform calculations based on the battery charge percentage, remaining charging duration, and vehicle priority coefficient to determine the vehicle basic weight;

[0014] Perform calculations based on the available power of the power grid, vehicle basic weight, and charging required power to determine the effective allocation power, and control each charging pile to operate with the corresponding effective allocation power.

[0015] Optionally, it further includes a step of obtaining the remaining charging duration, and this step includes:

[0016] Obtain the user input status;

[0017] Judge whether the user input status is consistent with the preset valid input status;

[0018] If the user input status is consistent with the valid input status, then obtain the input end time according to the valid input status, and determine the remaining charging duration according to the input end time and the current time point;

[0019] If the user input status is inconsistent with the valid input status, then obtain the charging operation account and the user start period;

[0020] Construct a historical interval on the preset time axis with the current time point as the rear end point and a width of the preset historical duration, and determine the single start period and the corresponding single moving period according to the charging operation account in the historical interval;

[0021] Analyze according to each single start period, single moving period, and user start period to determine the predicted moving period, and determine the remaining charging duration according to the predicted moving period and the current time point.

[0022] Optionally, the step of analyzing according to each single start period, single moving period, and user start period to determine the predicted moving period includes:

[0023] Define the single moving period corresponding to the single start period consistent with the user start period as the effective reference period;

[0024] Determine the actual elapsed duration according to the specific time point of the effective reference period and the current time point, and determine the effective trust value corresponding to the actual elapsed duration according to the preset trust matching relationship;

[0025] Perform calculations based on the effective trust values corresponding to different effective reference periods of each period to determine the period reference quantity;

[0026] Calculate based on the reference quantity in each time period to determine the time period reference proportion, and judge whether there is a situation where the time period reference proportion is greater than the preset effective habit proportion;

[0027] If there is a situation where the time period reference proportion is greater than the effective habit proportion, then define the corresponding single moving time period as the predicted moving time period;

[0028] If there is no situation where the time period reference proportion is greater than the effective habit proportion, then calculate based on the user's starting time period and the preset single fixed duration to determine the predicted moving time period.

[0029] Optionally, after determining the effective allocated power, the charging station management method based on the smart box further includes:

[0030] Obtain the reference demand power of each vehicle;

[0031] Judge whether all effective allocated powers are greater than the corresponding reference demand powers;

[0032] If all effective allocated powers are greater than the corresponding reference demand powers, then control each charging pile to operate according to the effective allocated power;

[0033] If all effective allocated powers are not greater than the corresponding reference demand powers, then define the charging pile corresponding to the situation where the effective allocated power is not greater than the reference demand power as the missing pile, and define the remaining charging piles as the complete piles;

[0034] Perform difference calculation based on each effective allocated power and the reference demand power to determine the demand difference power, and perform summation calculation based on all demand supplementary powers of the missing piles to determine the overall supplementary power;

[0035] Perform calculation based on the overall supplementary power, the vehicle basic weight, and the demand difference power of each complete pile to determine the demand adjustment power, and perform calculation based on the demand adjustment power and the effective allocated power to determine the adjusted allocated power;

[0036] Control the missing piles to operate at the corresponding reference demand power, and control the complete piles to operate at the corresponding adjusted allocated power.

[0037] Optionally, after each charging pile operates, the charging station management method based on the smart box further includes:

[0038] Construct a detection interval on the time axis with the starting time point of the charging pile starting to operate as the starting point and a width of the preset detection duration, and obtain the actual operating power of each charging pile at each time point in the detection interval;

[0039] Define the power of each charging pile during operation as the theoretical operation power, and calculate based on the actual operation power and the theoretical operation power to determine the power disturbance power;

[0040] Perform a summation calculation based on the power disturbance power at the same time point to determine the overall disturbance power;

[0041] Calculate based on the overall power of the power grid and the available power of the power grid to determine the anti-disturbance power;

[0042] Determine the overall disturbance power with the largest value according to the preset sorting rule, and calculate based on the overall disturbance power and the anti-disturbance power to determine the effective disturbance ratio.

[0043] Optionally, after determining the effective disturbance ratio, the charging station management method based on the intelligent box further includes:

[0044] Determine the permitted release power according to the anti-disturbance power and the effective disturbance ratio;

[0045] Perform a summation calculation based on the permitted release power and the available power of the power grid to update the available power of the power grid;

[0046] After updating the available power of the power grid, recalculate the theoretical operation power of each charging pile, and perform operation control on each charging pile according to the theoretical operation power.

[0047] In a second aspect, the present application provides a charging station management system based on an intelligent box, adopting the following technical solutions:

[0048] A charging station management system based on an intelligent box, including:

[0049] An acquisition module, configured to acquire the overall power of the power grid and the charging demand power of each current charging pile;

[0050] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0051] A judgment module, connected to the acquisition module and the processing module, for judging information;

[0052] The processing module calculates based on each charging demand power to determine the overall demand power, and calculates based on the overall power of the power grid and a preset anti-disturbance coefficient to determine the available power of the power grid;

[0053] The judgment module judges whether the overall demand power is greater than the available power of the power grid;

[0054] If the judgment module judges that the overall demand power is not greater than the available power of the power grid, the processing module controls each charging pile to operate with the corresponding charging demand power;

[0055] If the judgment module determines that the overall required power is greater than the available power of the power grid, the acquisition module obtains the battery charge percentage, remaining charging duration, and vehicle priority coefficient of each vehicle according to each charging pile;

[0056] The processing module calculates based on the battery charge percentage, remaining charging duration, and vehicle priority coefficient to determine the vehicle basic weight;

[0057] The processing module calculates based on the available power of the power grid, the vehicle basic weight, and the charging required power to determine the effective allocation power, and controls each charging pile to operate with the corresponding effective allocation power.

[0058] Thirdly, the present application provides a computer storage medium that can store corresponding programs and has the characteristic of improving the charging experience when a vehicle uses a charging station. The following technical solution is adopted:

[0059] A computer-readable storage medium stores a computer program that can be loaded and executed by a processor to perform any one of the above-mentioned charging station management methods based on an intelligent box.

[0060] In summary, the present application includes at least one of the following beneficial technical effects:

[0061] 1. When the power of the power grid cannot meet the power for each charging pile to operate normally at the same time, it can analyze the demand degree of the vehicles connected to each charging pile for charging operations to reasonably allocate the charging power, thereby improving the charging experience when a vehicle uses a charging station;

[0062] 2. It can analyze the charging habits of each vehicle to better determine the charging demand degree of each vehicle;

[0063] 3. It can release part of the power according to the actual fluctuations of the current power grid to better meet the charging demands of each vehicle. Description of the Drawings

[0064] Figure 1 is a flowchart of the charging station management method based on an intelligent box.

[0065] Figure 2 is a module flowchart of the charging station management method based on an intelligent box. Detailed Embodiments

[0066] In order to make the purpose, technical solutions and advantages of the present application clearer, the following is a further detailed description of the present application in combination with Figure 1 - Figure 2 and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] The following further describes the embodiments of the present application in conjunction with the accompanying drawings of the specification.

[0068] The embodiments of the present application disclose a charging station management method based on an intelligent box. Referring to Figure 1 , the method flow of the charging station management method based on the intelligent box includes the following steps:

[0069] Step S100: Obtain the overall power of the power grid and the charging demand power of each current charging pile.

[0070] The overall power of the power grid is all the power values available for use in the current power grid, and the charging demand power is the charging power that needs to be achieved when the vehicles connected to each charging pile charge in the set charging mode. Both can obtain data through the intelligent box on the charging station.

[0071] Step S101: Calculate according to each charging demand power to determine the overall demand power, and calculate according to the overall power of the power grid and the preset anti-disturbance coefficient to determine the available power of the power grid.

[0072] The overall demand power is the total power required when each charging pile charges according to the corresponding mode currently, which is obtained by adding up each charging demand power; the anti-disturbance coefficient is the power set by the staff to use part of the power for anti-power disturbance while the other power can be used normally. This value is between 0 and 1, for example, 0.9, that is, 10% of the power is reserved for anti-power disturbance. The available power of the power grid that can be used by all charging piles can be obtained by multiplying the overall power of the power grid by the anti-disturbance coefficient.

[0073] Step S102: Determine whether the overall demand power is greater than the available power of the power grid.

[0074] The purpose of the determination is to know whether the power of the current power grid can meet the charging requirements of each charging pile.

[0075] Step S1021: If the overall demand power is not greater than the available power of the power grid, control each charging pile to operate at the corresponding charging demand power.

[0076] When the overall demand power is not greater than the available power of the power grid, it means that the power of the power grid can meet the charging requirements of each charging pile. At this time, each charging pile can operate at the charging demand power.

[0077] Step S1022: If the overall demand power is greater than the available power of the power grid, obtain the battery power percentage, remaining charging duration, and vehicle priority coefficient of each vehicle according to each charging pile.

[0078] When the overall demand power is greater than the available power of the power grid, it means that it is impossible to meet the charging requirements of all charging piles, so further analysis is needed; the battery charge percentage is the ratio of the remaining power of the vehicle at present, that is, the SOC value; the remaining charging duration is the remaining duration value for charging the vehicle, and the end time point of the vehicle charging can be set manually by the staff or determined by referring to the method in steps S200 - S203; the vehicle priority coefficient is the coefficient value reflecting the priority degree of the vehicle during charging operations. For example, ordinary users have the lowest priority and VIP users have the highest priority, etc. Specifically, the management staff determines the priority levels of different vehicles in advance, and obtains the vehicle data through the intelligent box to judge the specific vehicle priority coefficient.

[0079] Step S103: Calculate according to the battery charge percentage, remaining charging duration, and vehicle priority coefficient to determine the vehicle base weight.

[0080] The vehicle base weight is a parameter reflecting the demand degree of an individual vehicle for charging operations. The larger this value is, the more necessary it is to charge the vehicle. The calculation formula is

[0081]

[0082] Where W i is the vehicle base weight of the i-th vehicle, SOC i is the battery charge percentage of the i-th vehicle, T i is the remaining charging duration of the i-th vehicle, U i is the vehicle priority coefficient of the i-th vehicle, and α, β, γ are adjustment coefficients set by the staff according to the actual situation, and it is necessary to ensure that α + β + γ = 1.

[0083] Step S104: Calculate according to the available power of the power grid, vehicle base weight, and charging demand power to determine the effective allocation power, and control each charging pile to operate with the corresponding effective allocation power.

[0084] The effective allocation power is the power allocated to each charging pile for the charging pile to operate. The calculation formula is

[0085]

[0086] Where P i is the effective allocation power of the charging pile corresponding to the i-th vehicle, P max is the charging demand power of the corresponding charging pile, P grid is the available power of the power grid, and n is the number of all charging piles that need to be used.

[0087] It also includes the step of obtaining the remaining charging duration, and this step includes:

[0088] Step S200: Obtain the user input status.

[0089] The user input status is the status of whether the user inputs the time point when to end charging when using the charging pile.

[0090] Step S201: Determine whether the user input status is consistent with the preset valid input status.

[0091] The valid input status is the user input status when the user inputs the charging end time point. The purpose of the determination is to know whether the remaining charging duration can be directly determined.

[0092] Step S2011: If the user input status is consistent with the valid input status, obtain the input end time according to the valid input status, and determine the remaining charging duration according to the input end time and the current time point.

[0093] When the user input status is consistent with the valid input status, it indicates that the user has input the time point to end charging. At this time, obtain the input end time. The interval duration between the input end time and the current time point is the remaining charging duration that the vehicle can still be charged.

[0094] Step S2012: If the user input status is inconsistent with the valid input status, obtain the charging operation account and the user start period.

[0095] When the user input status is inconsistent with the valid input status, it means that the time point when the current user needs to end charging cannot be directly known. Therefore, further analysis is required; the charging operation account is the user account currently using the charging pile, and the user start period is the time period when the current user uses the charging pile. For the convenience of data analysis, the specific time point is not analyzed, only the time period is analyzed. For example, the time period is distinguished in hours.

[0096] Step S202: Construct a historical interval on the preset time axis with the current time point as the rear end point and a width of the preset historical duration, and determine the single start period and the corresponding single moving period according to the charging operation account in the historical interval.

[0097] The time axis is an axis formed by combining each time point. This axis points from the passed time points to the time points that have not yet been reached. Among them, the passed time points are on the left side of the axis, and the left side of the axis is defined as the front side of the time axis; the historical duration is the duration set by the staff to obtain the historical charging data of each user. Generally, this duration is the interval duration between the time when the charging station is put into use and the current time point. By constructing a historical interval, it is convenient to obtain and analyze the data within the historical duration; the single starting period is the time period when the current user charges within the historical interval. This time period is only distinguished by the time period and does not include the year, month, and day. The single moving period is the time period when the vehicle corresponding to the current user is disconnected from the charging pile.

[0098] Step S203: Analyze according to each single starting period, single moving period, and user starting period to determine the predicted moving period, and determine the remaining charging duration according to the predicted moving period and the current time point.

[0099] The predicted moving period is the time period predicted after data analysis when the user will end during the current charging process. For the specific analysis process, refer to Step S300 - Step S3032. At this time, the interval duration between the predicted moving period and the current time point is the remaining charging duration.

[0100] The steps to analyze according to each single starting period, single moving period, and user starting period to determine the predicted moving period include:

[0101] Step S300: Define the single moving period corresponding to the single starting period that is consistent with the user starting period as the effective reference period.

[0102] When the single starting period is consistent with the user starting period, it indicates that the charging habit of this charging in the historical interval may be similar to the current one. Therefore, it has reference significance, and thus it is defined as the effective reference period to distinguish different single moving periods for subsequent analysis.

[0103] Step S301: Determine the actual elapsed duration according to the specific time point of the effective reference period and the current time point, and determine the effective trust value corresponding to the actual elapsed duration according to the preset trust matching relationship.

[0104] The specific time point of the effective reference period is the specific time after including the year, month, and day. The actual elapsed duration is the duration value of the interval since the corresponding data was generated. The effective trust value is the parameter value reflecting the data reliability. The smaller the actual elapsed duration, the more it conforms to the current user's behavior habit, and the stronger the reliability of the corresponding data. The trust matching relationship between the two is determined by the staff through multiple experiments in advance, and its range is controlled between 0.5 - 1.5.

[0105] Step S302: Calculate based on the effective trust values corresponding to different effective reference periods in each period to determine the period reference quantity.

[0106] The period reference quantity is the sum of the corresponding effective trust values under all the same effective reference periods.

[0107] Step S303: Calculate based on the period reference quantities of each period to determine the period reference ratio, and determine whether there is a situation where the period reference ratio is greater than the preset effective habit ratio.

[0108] The period reference ratio is the ratio of the period reference quantity of a single effective reference period to the total period reference quantity of all periods. The effective habit ratio is the minimum period reference ratio set by the staff to better reflect that a single user has a certain charging habit. The purpose of the judgment is to know whether the user has a charging habit.

[0109] Step S3031: If there is a situation where the period reference ratio is greater than the effective habit ratio, then define the corresponding single movement period as the predicted movement period.

[0110] When there is a situation where the period reference ratio is greater than the effective habit ratio, it means that the user has a certain charging habit, that is, the user has a high probability of disconnecting the vehicle from the charging pile during the single movement period. At this time, just define the corresponding single movement period as the predicted movement period. Using this method can meet the charging situation prediction of people going to work daily and improve the accuracy of data analysis.

[0111] Step S3032: If there is no situation where the period reference ratio is greater than the effective habit ratio, then calculate based on the user's starting period and the preset single fixed duration to determine the predicted movement period.

[0112] When there is no situation where the period reference ratio is greater than the effective habit ratio, it means that the user has no fixed charging habit. At this time, extend the user's starting period backward by the single fixed duration to determine the predicted movement period. The single fixed duration is a fixed value set by the staff.

[0113] After the effective distribution power is determined, the charging station management method based on the intelligent box further includes:

[0114] Step S400: Obtain the benchmark demand power of each vehicle.

[0115] The benchmark demand power is the most basic charging power required for a single vehicle during the charging process. Different vehicles require different benchmark demand powers.

[0116] Step S401: Determine whether all the effective allocated powers are greater than the corresponding reference demand powers.

[0117] The purpose of the determination is to know whether each charging pile can meet the minimum charging power requirement.

[0118] Step S4011: If all the effective allocated powers are greater than the corresponding reference demand powers, control each charging pile to operate according to the effective allocated power.

[0119] When all the effective allocated powers are greater than the corresponding reference demand powers, it means that all the charging piles can meet the minimum charging power requirement. At this time, just operate with the set effective allocated power.

[0120] Step S4012: If not all the effective allocated powers are greater than the corresponding reference demand powers, define the charging piles corresponding to the effective allocated powers not greater than the reference demand powers as missing piles, and define the remaining charging piles as complete piles.

[0121] When not all the effective allocated powers are greater than the corresponding reference demand powers, it means that there are charging piles that cannot meet the minimum charging power requirement. Therefore, further analysis is needed; define the missing piles and complete piles to distinguish different charging piles for subsequent analysis.

[0122] Step S402: Calculate the difference to determine the demand difference power according to each effective allocated power and the reference demand power, and calculate the sum according to all the demand supplementary powers of the missing piles to determine the overall supplementary power.

[0123] The demand difference power is the difference between the effective allocated power of the charging pile and the reference demand power, and this difference is an absolute value. The overall supplementary power is the power that needs to be transferred from the complete piles for the missing piles to use, which is determined by adding up all the demand supplementary powers of the missing piles.

[0124] Step S403: Calculate according to the overall supplementary power, the vehicle basic weight, and the demand difference power of each complete pile to determine the demand adjustment power, and calculate according to the demand adjustment power and the effective allocated power to determine the adjusted allocation power.

[0125] The demand adjustment power is the power value that each complete pile needs to transfer away, and the calculation formula is

[0126]

[0127] where P out is the demand adjustment power, P needTo supplement power as a whole, m is the number of all complete charging piles; when the required adjusted power of each complete charging pile is greater than the required difference power of the charging pile, the required adjusted power is marked with the required difference power of the charging pile to reduce the situation that the charging pile cannot meet the minimum charging requirement after power adjustment. At this time, the insufficient power value of the complete charging pile is recalculated by the remaining complete charging piles to update the required adjusted power of each charging pile; the adjusted distribution power required for the operation of the complete charging pile can be obtained by subtracting the corresponding required adjusted power from the effective distribution power of the complete charging pile.

[0128] Step S404: Control the missing charging pile to operate at the corresponding reference required power, and control the complete charging pile to operate at the corresponding adjusted distribution power.

[0129] By controlling each charging pile to operate at the corresponding power, each vehicle can be charged better.

[0130] After each charging pile operates, the charging station management method based on the intelligent box further includes:

[0131] Step S500: Construct a detection interval on the time axis with the starting time point of the charging pile operation as the starting point and a width of a preset detection duration, and obtain the actual operation power of each charging pile at each time point in the detection interval.

[0132] The detection duration is a fixed duration set by the staff, such as half an hour. By constructing the detection interval, it is convenient to obtain and analyze the data within the detection time; the actual operation power is the charging power during the actual operation of the charging pile.

[0133] Step S501: Define the power of each charging pile operation as the theoretical operation power, and calculate based on the actual operation power and the theoretical operation power to determine the power disturbance.

[0134] The theoretical operation power is the output power set by the charging pile under theoretical conditions, that is, the reference required power of the missing charging pile, the adjusted distribution power of the complete charging pile when there is a missing charging pile, and the effective distribution power when there is no missing charging pile; the power disturbance is the deviation power generated due to power disturbance, which is determined by calculating the difference between the actual operation power and the theoretical operation power.

[0135] Step S502: Calculate the sum of the power disturbances at the same time point to determine the overall disturbance power.

[0136] The overall disturbance power is the power disturbance borne by the power grid at the same time point, which is determined by adding all the power disturbances at the same time point.

[0137] Step S503: Calculate based on the overall power of the power grid and the available power of the power grid to determine the anti-disturbance power.

[0138] The anti-disturbance power is the power value reserved by the power grid for anti-disturbance, which is determined by subtracting the available power of the power grid from the overall power of the power grid.

[0139] Step S504: Determine the overall disturbance power with the largest value according to the preset sorting rule, and calculate according to the overall disturbance power and the anti-disturbance power to determine the effective disturbance ratio.

[0140] The sorting rule is a method set by the staff to sort the numerical values, such as the bubble method. Through the sorting rule, the overall disturbance power with the largest value can be determined, that is, the maximum disturbance situation that will occur in the power grid under the current circumstances. At this time, by dividing the overall disturbance power with the largest value by the anti-disturbance power, the effective disturbance ratio reflecting the use of the reserved power can be obtained, so that the management personnel can know the specific use situation of the current power grid.

[0141] After the effective disturbance ratio is determined, the charging station management method based on the intelligent box further includes:

[0142] Step S600: Determine the permitted release power according to the anti-disturbance power and the effective disturbance ratio.

[0143] The permitted release power is the power value that can release the reserved power for use by the charging pile. It can be obtained by subtracting the overall disturbance power with the largest value from the anti-disturbance power and then multiplying by a set multiple. The setting of this multiple is less than 1, generally in the range of 0.7 - 0.9.

[0144] Step S601: Perform a summation calculation according to the permitted release power and the available power of the power grid to update the available power of the power grid.

[0145] By adding the permitted release power and the available power of the power grid, the available power of the power grid can be updated, so that while ensuring the safety of the power grid, more electricity can be used for the charging pile.

[0146] Step S602: After the available power of the power grid is updated, recalculate the theoretical operating power of each charging pile, and perform operating control on each charging pile according to the theoretical operating power.

[0147] By recalculating the theoretical operating power of each charging pile, the operating update control of each charging pile can be realized, so that each charging pile can operate better.

[0148] Refer to Figure 2 , Based on the same inventive concept, an embodiment of the present invention provides a charging station management system based on an intelligent box, including:

[0149] An acquisition module, configured to acquire the overall power of the power grid and the charging demand power of each current charging pile;

[0150] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0151] A judgment module, connected to the acquisition module and the processing module, for judging information;

[0152] The processing module calculates according to each charging demand power to determine the overall demand power, and calculates according to the overall power of the power grid and a preset anti-disturbance coefficient to determine the available power of the power grid;

[0153] The judgment module judges whether the overall demand power is greater than the available power of the power grid;

[0154] If the judgment module judges that the overall demand power is not greater than the available power of the power grid, the processing module controls each charging pile to operate with the corresponding charging demand power;

[0155] If the judgment module judges that the overall demand power is greater than the available power of the power grid, the acquisition module acquires the battery charge percentage, remaining charging duration, and vehicle priority coefficient of each vehicle according to each charging pile;

[0156] The processing module calculates according to the battery charge percentage, remaining charging duration, and vehicle priority coefficient to determine the vehicle basic weight;

[0157] The processing module calculates according to the available power of the power grid, the vehicle basic weight, and the charging demand power to determine the effective allocation power, and controls each charging pile to operate with the corresponding effective allocation power;

[0158] A remaining charging duration determination module, for determining and acquiring the remaining charging duration of the vehicle;

[0159] A predicted moving time period determination module, for accurately determining the predicted moving time period;

[0160] A reference demand determination module, for determining the reference charging demand of each vehicle;

[0161] A power disturbance analysis module, for analyzing and processing the power disturbance situation after the charging pile operates;

[0162] A power release module, for releasing the excess power.

[0163] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above division of each functional module is used as an example. In actual applications, the above functions can be assigned to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. For the specific working processes of the systems, devices, and units described above, reference can be made to the corresponding processes in the foregoing method embodiments, which will not be elaborated herein.

[0164] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded and executed by a processor to perform a charging station management method based on an intelligent box.

[0165] Computer storage media include, for example, various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

Claims

1. A charging station management method based on an intelligent box, characterized in that, including: Obtaining the overall power of the power grid and the charging demand power of each current charging pile; Calculating according to each charging demand power to determine the overall demand power, and calculating according to the overall power of the power grid and a preset anti-disturbance coefficient to determine the available power of the power grid; Judging whether the overall demand power is greater than the available power of the power grid; If the overall demand power is not greater than the available power of the power grid, controlling each charging pile to operate with the corresponding charging demand power; If the overall demand power is greater than the available power of the power grid, obtaining the battery power percentage, remaining charging duration and vehicle priority coefficient of each vehicle according to each charging pile; Calculating according to the battery power percentage, remaining charging duration and vehicle priority coefficient to determine the vehicle basic weight; Calculating according to the available power of the power grid, vehicle basic weight and charging demand power to determine the effective allocation power, and controlling each charging pile to operate with the corresponding effective allocation power.

2. The charging station management method based on the intelligent box according to claim 1, wherein It further includes a step of obtaining the remaining charging duration, and this step includes: Obtaining the user input state; Judging whether the user input state is consistent with a preset valid input state; If the user input state is consistent with the valid input state, obtaining the input end time according to the valid input state, and determining the remaining charging duration according to the input end time and the current time point; If the user input state is inconsistent with the valid input state, obtaining the charging operation account and the user start time period; Constructing a historical interval on a preset time axis with the current time point as the rear end point and a width of a preset historical duration, and determining the single start time period and the corresponding single moving time period according to the charging operation account in the historical interval; Analyzing according to each single start time period, single moving time period and user start time period to determine the predicted moving time period, and determining the remaining charging duration according to the predicted moving time period and the current time point.

3. The charging station management method based on an intelligent box according to claim 2, wherein, The step of analyzing according to each single start time period, single moving time period and user start time period to determine the predicted moving time period includes: Defining the single moving time period corresponding to the single start time period consistent with the user start time period as the effective reference time period; Determining the actual elapsed duration according to the specific time point of the effective reference time period and the current time point, and determining the effective trust value corresponding to the actual elapsed duration according to a preset trust matching relationship; Calculating according to the effective trust values corresponding to the effective reference time periods of different time periods to determine the time period reference quantity; Calculating according to each time period reference quantity to determine the time period reference proportion, and judging whether there is a situation where the time period reference proportion is greater than a preset effective habit proportion; If there is a situation where the time period reference proportion is greater than the effective habit proportion, defining the corresponding single moving time period as the predicted moving time period; If there is no situation where the time period reference proportion is greater than the effective habit proportion, calculating according to the user start time period and a preset single fixed duration to determine the predicted moving time period.

4. The charging station management method based on an intelligent box according to claim 1, wherein After the effective allocation power is determined, the charging station management method based on the intelligent box further includes: Obtaining the benchmark demand power of each vehicle; Judging whether all effective allocation powers are greater than the corresponding benchmark demand powers; If all the effective allocated powers are greater than the corresponding reference demand powers, then control each charging pile to operate according to the effective allocated powers; If all the effective allocated powers are not all greater than the corresponding reference demand powers, then define the charging piles corresponding to the effective allocated powers that are not greater than the reference demand powers as missing piles, and define the remaining charging piles as complete piles; Perform a difference calculation based on each effective allocated power and the reference demand power to determine the demand difference power, and perform a summation calculation based on all the demand supplementary powers of the missing piles to determine the overall supplementary power; Perform calculations based on the overall supplementary power, the vehicle base weight, and the demand difference powers of each complete pile to determine the demand adjustment power, and perform calculations based on the demand adjustment power and the effective allocated power to determine the adjusted allocated power; Control the missing piles to operate at the corresponding reference demand powers, and control the complete piles to operate at the corresponding adjusted allocated powers.

5. The charging station management method based on an intelligent box according to claim 4, wherein, After each charging pile operates, the charging station management method based on the intelligent box further includes: Construct a detection interval on the time axis with the starting time point when the charging pile starts operating as the starting point and a width of a preset detection duration, and obtain the actual operating power of each charging pile at each time point in the detection interval; Define the power at which each charging pile operates as the theoretical operating power, and perform calculations based on the actual operating power and the theoretical operating power to determine the power disturbance; Perform a summation calculation based on the power disturbances at the same time point to determine the overall disturbance power; Perform calculations based on the overall power of the power grid and the available power of the power grid to determine the anti-disturbance power; Determine the overall disturbance power with the largest value according to a preset sorting rule, and perform calculations based on this overall disturbance power and the anti-disturbance power to determine the effective disturbance ratio.

6. The charging station management method based on an intelligent box according to claim 5, wherein, After the effective disturbance ratio is determined, the charging station management method based on the intelligent box further includes: Determine the permitted release power according to the anti-disturbance power and the effective disturbance ratio; Perform a summation calculation based on the permitted release power and the available power of the power grid to update the available power of the power grid; After the available power of the power grid is updated, recalculate the theoretical operating power of each charging pile, and control the operation of each charging pile according to the theoretical operating power.

7. A charging station management system based on an intelligent box, characterized in that, Includes: An acquisition module for acquiring the overall power of the power grid and the charging demand power of each current charging pile; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected to the acquisition module and the processing module, for judging information; The processing module performs calculations based on each charging demand power to determine the overall demand power, and performs calculations based on the overall power of the power grid and a preset anti-disturbance coefficient to determine the available power of the power grid; The judgment module judges whether the overall demand power is greater than the available power of the power grid; If the judgment module judges that the overall demand power is not greater than the available power of the power grid, then the processing module controls each charging pile to operate at the corresponding charging demand power; If the judgment module judges that the overall demand power is greater than the available power of the power grid, then the acquisition module acquires the battery power percentage, the remaining charging duration, and the vehicle priority coefficient of each vehicle according to each charging pile; The processing module calculates based on the battery power percentage, the remaining charging duration, and the vehicle priority coefficient to determine the vehicle base weight; The processing module calculates based on the available grid power, the vehicle base weight, and the charging demand power to determine the effective allocation power, and controls each charging pile to operate with the corresponding effective allocation power.

8. A computer-readable storage medium, characterized in that, A computer program is stored that can be loaded and executed by a processor for the charging station management method based on an intelligent box described in any one of claims 1 to 6.

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