A charging strategy optimization method and system based on big data

Abstract

The present invention discloses a method and system for optimizing a charging strategy based on big data. The method includes: dividing the vehicle parking time interval into multiple first time intervals based on a preset time interval; analyzing the charging requests to formulate a charging plan for the vehicles to be charged; when the charging plan for the vehicles to be charged does not meet the vehicle charging conditions, in the slow charging mode, determining multiple power adjustment data according to the number of vehicles being charged in each first time interval, and analyzing the multiple power adjustment data to determine a charging adjustment plan; in the fast charging mode, calculating a third adjustment score for each first time interval, and analyzing each first time interval in turn according to the order from large to small of the third adjustment scores to determine a charging adjustment plan; and updating the remaining power supply of the power grid. The present invention optimizes the charging load by reasonably arranging the charging time period, reduces the pressure on the power grid, and improves the stability and safety of the power grid operation.

Description

Technical Field

[0001] The present application relates to the technical field of new energy vehicle charging, and more specifically, to a method and system for optimizing charging strategies based on big data. Background Art

[0002] With the rapid development of the electric vehicle industry, the charging demand has increased sharply, posing higher requirements for the efficient operation of charging facilities and the stable operation of the power grid. Traditional charging strategies are often based on static planning, making it difficult to adapt to changing charging environments, user needs, and grid loads, lacking real-time performance, flexibility, and intelligence, resulting in problems such as low utilization rate of charging facilities, large fluctuations in grid loads, and poor user experience.

[0003] Therefore, there are defects in the existing technology and urgent improvements are needed. Summary of the Invention

[0004] In view of the above problems, the object of the present invention is to provide a method and system for optimizing charging strategies based on big data, which can relieve the pressure during peak grid hours, improve the stability and safety of grid operation by reasonably arranging charging periods and optimizing charging loads.

[0005] The first aspect of the present invention provides a method for optimizing a charging strategy based on big data, including:

[0006] Obtaining charging request data of a vehicle to be charged; the charging request data includes the charging mode selected by the user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval, and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode;

[0007] Dividing the vehicle parking time interval into multiple first time intervals based on a preset time interval;

[0008] Analyzing according to the charging request to formulate a charging plan for the vehicle to be charged, and charging the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan;

[0009] When the charging plan of the vehicle to be charged does not meet the vehicle charging conditions, analyze according to the charging mode selected by the user. When the user selects the slow charging mode, determine multiple power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the multiple power adjustment data to determine a charging adjustment plan;

[0010] When the user selects the fast charging mode, calculate the third adjustment score for each first time interval, and analyze each first time interval in order from largest to smallest third adjustment score to determine a charging adjustment plan;

[0011] Adjust the charging plans of the vehicle to be charged and the vehicle being charged according to the charging adjustment plan, and update the remaining power supply of the power grid in the corresponding first time interval.

[0012] In this solution, the analysis based on the charging request to formulate the charging plan for the vehicle to be charged includes:

[0013] When the user selects the slow charging mode, determine whether the vehicle to be charged meets the slow charging conditions according to the required power of the vehicle to be charged, the vehicle parking time interval, and the rated slow charging power;

[0014] If so, determine the slow charging time interval according to the remaining power supply of the power grid and the vehicle parking time interval, and formulate a slow charging plan in combination with the rated slow charging power;

[0015] If not, ask the user whether to perform fast charging;

[0016] When the user selects the fast charging mode, calculate the power supply score for each first time interval according to the remaining power supply of the power grid, the maximum fast charging power of the vehicle to be charged, and the electricity price;

[0017] Determine one or more first time intervals as the fast charging time intervals of the vehicle to be charged in the order of the power supply score from large to small, and determine the fast charging power for each fast charging time interval according to the remaining power of the vehicle at the start time of the fast charging time interval, and formulate a fast charging plan.

[0018] In this solution, the determination of the slow charging time interval according to the remaining power supply of the power grid and the vehicle parking time interval includes:

[0019] Filter the first time intervals in which the remaining power supply of the power grid is less than the rated slow charging power of the vehicle to be charged, and determine one or more sets of first time interval sets according to the continuous first time intervals;

[0020] Divide the one or more sets of first time interval sets according to the electricity price adjustment time to determine one or more sets of second time interval sets;

[0021] Calculate the first charging score for each set of second time intervals based on the time length and electricity price of the time interval set;

[0022] Determine the required charging time of the vehicle according to the ratio of the required power of the vehicle and the rated slow charging power;

[0023] Accumulate the time lengths of the second time interval set in descending order of the first charging score. When the accumulated time length is greater than or equal to the charging time required by the vehicle, intercept the last second time interval set participating in the accumulation according to the first time difference between the accumulated time length and the charging time required by the vehicle, and determine the first time interval within the second time interval set participating in the accumulation as the slow charging time interval.

[0024] In this solution, determining one or more first time intervals as the fast charging time intervals of the vehicle to be charged in descending order of the power supply score, and determining the fast charging power of each fast charging time interval according to the remaining power of the vehicle at the start time of the fast charging time interval, formulating a fast charging plan, including:

[0025] Filter the first time intervals with a power supply score less than the preset score threshold;

[0026] Determine the first first time interval as the second time interval in chronological order;

[0027] Determine the minimum power between the remaining power supply power of the power grid within the second time interval and the maximum fast charging power of the vehicle to be charged as the first charging power of the second time interval;

[0028] Calculate the charging amount of the second time interval. When the charging amount of the second time interval is greater than or equal to the power required by the vehicle, determine the second time interval as the fast charging time interval, and determine the first charging power as the fast charging power of the corresponding fast charging time interval;

[0029] When the charging amount of the second time interval is less than the power required by the vehicle, predict the battery temperature data at the end time of the second time interval according to the first charging power, time length of the second time interval, and the soc value of the vehicle battery at the start time of the interval;

[0030] When the battery temperature data is less than the first preset battery temperature threshold, determine the next first time interval as the next second time interval in chronological order, and determine the first charging power of the next second time interval;

[0031] When the battery temperature data is greater than or equal to the first preset battery temperature threshold, predict the cooling time interval when the battery temperature data drops to the second preset battery temperature threshold according to the external environment data, determine the first first time interval after the cooling time interval as the next second time interval, and determine the first charging power of the next second time interval;

[0032] Accumulate the charging amounts for all the second time intervals. When the accumulated charging amount is greater than or equal to the power required by the vehicle, determine all the second time intervals as fast charging time intervals, and determine the first charging power for each second time interval as the fast charging power for the corresponding fast charging time interval.

[0033] In this solution, when the user selects the slow charging mode, determine a plurality of power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the plurality of power adjustment data to determine a charging adjustment plan, including:

[0034] Calculate the first adjustment score for each first time interval according to the rated slow charging power of the vehicle to be charged, the power of the remaining power of the power grid, and the electricity price;

[0035] Determine the first time intervals with the first adjustment score greater than the preset adjustment score threshold as the third time intervals;

[0036] Determine a plurality of power adjustment data according to the number of vehicles being charged in each third time interval; each power adjustment data corresponds to the slow charging time interval and the rated slow charging power of a vehicle being charged;

[0037] Calculate the second adjustment score for each power adjustment data;

[0038] Select the power adjustment data for analysis in order from largest to smallest second adjustment score, and obtain the time position of the slow charging time interval of the vehicle being charged corresponding to the power adjustment data in the corresponding first time interval set;

[0039] When the slow charging time interval of the vehicle being charged corresponding to the power adjustment data is at both ends of the corresponding first time interval set, the power adjustment data meets the adjustment conditions;

[0040] On the contrary, divide the corresponding first time interval set according to the slow charging time interval of the vehicle being charged corresponding to the power adjustment data, and judge whether the time lengths of the two sub-time interval sets obtained after division are both greater than the preset time length threshold;

[0041] If so, the power adjustment data meets the adjustment conditions; if not, it does not meet the adjustment conditions, and filter the power adjustment data;

[0042] When the power adjustment data meets the adjustment conditions, adjust the slow charging time interval of the vehicle being charged corresponding to the power adjustment data to the first time interval connected end to end at the end of the corresponding first time interval set, and determine the third time interval corresponding to the power adjustment data as the slow charging time interval of the vehicle to be charged.

[0043] In this solution, it also includes:

[0044] The calculation method of the second adjustment score m 2 is expressed by the formula as follows: ;

[0045] wherein, m 1 is the first adjustment score, p L1 is the rated slow charging power of the vehicle being charged corresponding to the power adjustment data, p 0 is the system - preset supplementary power, p RP is the remaining power supply of the power grid, k 1 is the adjustment coefficient of the second adjustment score.

[0046] In this solution, when the user selects the fast - charging mode, calculate the third adjustment score for each first time interval, and analyze each first time interval in descending order of the third adjustment score to determine the charging adjustment plan, including:

[0047] Calculate the third adjustment score for each first time interval according to the minimum fast - charging power of the vehicle to be charged, the remaining power supply of the power grid in the first time interval, and the minimum time interval between the first time interval and the occupied time interval;

[0048] Determine the first time interval with the largest third adjustment score as the fourth time interval;

[0049] Calculate the second time difference between the fourth time interval and the previous occupied time interval of the vehicle to be charged, and calculate the third time difference between the fourth time interval and the next occupied time interval of the vehicle to be charged;

[0050] Predict the battery temperature data at the start time of the fourth time interval according to the battery temperature data, the external environment data at the end time of the previous occupied time interval, and the second time difference;

[0051] Calculate the maximum battery temperature data at the start time of the next occupied time interval according to the first preset battery temperature threshold and the fast - charging power of the next occupied time interval, and predict the maximum battery temperature data at the end time of the fourth time interval in combination with the third time difference;

[0052] Analyze according to the battery temperature data at the start time and the maximum battery temperature data at the end time of the fourth time interval to determine the first predicted charging power of the vehicle to be charged within the fourth time interval;

[0053] When the first predicted charging power is greater than the minimum fast - charging power of the vehicle to be charged, and less than the sum of the remaining power supply of the power grid and the maximum value of the fast - charging power of the vehicle being charged within the fourth time interval, the fourth time interval meets the adjustment condition;

[0054] Determine the charging vehicle whose fast charging power minimum value is greater than the difference between the first predicted charging power and the remaining grid power supply as the adjustment vehicle;

[0055] Adjust the fast charging time interval of the adjustment vehicle according to the remaining fast charging power of the grid in other first time intervals; Determine the fourth time interval as the fast charging power interval of the vehicle to be charged, and determine the first predicted charging power as the corresponding fast charging power;

[0056] When the fourth time interval does not meet the adjustment condition, determine the next first time interval as the fourth time interval in descending order of the third adjustment score, and perform adjustment verification again.

[0057] This solution also includes:

[0058] When the power adjustment condition of the fast charging mode is still not met after all first time intervals are analyzed, calculate the fourth adjustment score for each fast charging time interval according to the maximum fast charging power of the vehicle to be charged, the fast charging power in the fast charging time interval, and the remaining grid power supply;

[0059] Determine the fast charging time interval with the maximum fourth adjustment score as the fifth time interval;

[0060] Predict the maximum battery temperature data at the end of the fifth time interval according to the fourth time difference between the fifth time interval and the next fast charging time interval of the vehicle to be charged and the maximum battery temperature data at the start time of the next fast charging time interval;

[0061] Analyze according to the battery temperature data at the start time of the fifth time interval and the maximum battery temperature data at the end time, and determine the second predicted charging power of the vehicle to be charged within the fifth time interval;

[0062] Determine the charging vehicle whose fast charging power minimum value is greater than the difference between the second predicted charging power and the fast charging power of the vehicle to be charged in the fifth time interval as the adjustment vehicle;

[0063] Update the fast charging power of the vehicle to be charged in the fifth time interval according to the second predicted charging power.

[0064] This solution also includes:

[0065] Input the required power of the charging vehicle and the vehicle parking time interval into the preset vehicle charging cost prediction model, and analyze in combination with the required power of other charging vehicles and the vehicle parking time interval to determine the maximum charging cost of the charging vehicle;

[0066] Calculate the predicted charging cost of the charging vehicle according to the charging time interval, charging power, and electricity price of the charging vehicle;

[0067] When the predicted charging cost is greater than the maximum charging cost, a prohibition adjustment mark is made for the vehicle being charged.

[0068] The second aspect of the present invention provides a charging strategy optimization system based on big data, including:

[0069] A data acquisition module for acquiring charging request data of a vehicle to be charged; the charging request data includes a charging mode selected by a user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval, and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode;

[0070] A time interval division module for dividing the vehicle parking time interval into a plurality of first time intervals based on a preset time interval;

[0071] A charging plan formulation module for analyzing according to the charging request, formulating a charging plan for the vehicle to be charged, and charging the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan;

[0072] A charging plan adjustment module for analyzing according to the charging mode selected by the user when the charging plan of the vehicle to be charged does not meet the vehicle charging conditions. When the user selects the slow charging mode, a plurality of power adjustment data are determined according to the number of vehicles being charged in each first time interval, and a charging adjustment plan is determined by analyzing the plurality of power adjustment data; when the user selects the fast charging mode, a third adjustment score of each first time interval is calculated, and each first time interval is analyzed in turn according to the order from large to small of the third adjustment score to determine a charging adjustment plan;

[0073] A grid remaining power supply monitoring module for adjusting the charging plans of the vehicle to be charged and the vehicles being charged according to the charging adjustment plan, and updating the grid remaining power supply of the corresponding first time interval.

[0074] The present invention discloses a method and system for optimizing a charging strategy based on big data. The method includes: dividing the vehicle parking time interval into multiple first time intervals based on a preset time interval; analyzing the charging request to formulate a charging plan for the vehicle to be charged; when the charging plan for the vehicle to be charged does not meet the vehicle charging conditions, in the slow charging mode, determining multiple power adjustment data according to the number of vehicles being charged in each first time interval, and analyzing the multiple power adjustment data to determine a charging adjustment plan; in the fast charging mode, calculating the third adjustment score for each first time interval, and analyzing each first time interval in order from largest to smallest according to the third adjustment score to determine a charging adjustment plan; updating the remaining power supply of the power grid. The present invention optimizes the charging load by reasonably arranging the charging time period, reduces the pressure on the power grid, and improves the stability and safety of the power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 FIG. shows a flowchart of a method for optimizing a charging strategy based on big data provided by the present invention;

[0076] Figure 2 FIG. shows a block diagram of a system for optimizing a charging strategy based on big data provided by the present invention. DETAILED DESCRIPTION

[0077] In order to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0078] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0079] Figure 1 FIG. shows a flowchart of a method for optimizing a charging strategy based on big data provided by the present invention.

[0080] As Figure 1 shown, the present invention discloses a method for optimizing a charging strategy based on big data, including:

[0081] S102, obtaining charging request data of the vehicle to be charged; the charging request data includes the charging mode selected by the user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval, and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode;

[0082] S104, divide the vehicle parking time interval into multiple first time intervals based on a preset time interval;

[0083] S106, analyze according to the charging request, formulate a charging plan for the vehicle to be charged, and charge the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan;

[0084] S108, when the charging plan of the vehicle to be charged does not meet the vehicle charging conditions, analyze according to the charging mode selected by the user. When the user selects the slow charging mode, determine multiple power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the multiple power adjustment data to determine the charging adjustment plan;

[0085] S110, when the user selects the fast charging mode, calculate the third adjustment score of each first time interval, analyze each first time interval in turn according to the order from large to small of the third adjustment score, and determine the charging adjustment plan;

[0086] S112, adjust the charging plans of the vehicle to be charged and the vehicles being charged according to the charging adjustment plan, and update the remaining power supply of the power grid in the corresponding first time interval.

[0087] According to the embodiment of the present invention, first divide the vehicle parking time interval into multiple first time intervals through a preset time interval (such as taking the whole hour as the division standard). Among them, the preset time interval is set by those skilled in the art according to actual needs.

[0088] When the vehicle to be charged is charging, if the charging mode selected by the user is the slow charging mode, first judge whether the slow charging conditions are met. If so, determine one or more sets of second time interval sets according to the remaining power supply of the power grid, the rated slow charging power of the vehicle to be charged, and the electricity price. Select a first time interval within one or more sets of second time interval sets as the slow charging time interval according to the first charging score and the required power of the vehicle, and formulate a slow charging plan for the vehicle to be charged. When the user selects the fast charging mode, determine the first charging power of the second time interval according to the remaining power supply of the power grid and the maximum fast charging power of the vehicle to be charged, and determine the next second time interval through the battery temperature data at the end time of the second time interval. When the cumulative charging amount in the second time interval is greater than or equal to the required power of the vehicle, determine all the second time intervals as the fast charging time intervals, determine the first charging power of each second time interval as the fast charging power of the corresponding fast charging time interval, and determine the fast charging plan for the vehicle to be charged.

[0089] When the charging plan of the vehicle to be charged does not meet the vehicle charging conditions, that is, when the charging amount in the charging time interval (including slow charging time and fast charging time) is less than the required power of the vehicle, the charging time interval of the vehicle being charged is adjusted. When the user selects the slow charging mode, calculate the second adjustment score for each power adjustment data, and sequentially select the power adjustment data for analysis in descending order of the second adjustment score, verify whether the power adjustment data meets the adjustment conditions, and adjust the slow charging time interval of the vehicle being charged corresponding to the power adjustment data that meets the adjustment conditions. When the user selects the fast charging mode, calculate the third adjustment score for each first time interval, determine the fourth time interval with the largest third adjustment score, calculate the first predicted charging power of the vehicle to be charged in the fourth time interval according to the second time difference and the third time difference between the fourth time interval and the adjacent occupied time intervals of the vehicle to be charged, and adjust the fast charging time interval of the vehicle being charged corresponding to the minimum fast charging power greater than the difference between the first predicted charging power and the remaining power supply of the power grid in the fourth time interval. When the power adjustment conditions for the fast charging mode are still not met after all the first time intervals are analyzed, adjust the fast charging power of the vehicle to be charged occupying the fast charging time interval. If the adjustment still does not meet the power adjustment conditions for the fast charging mode, remind the user through device terminals such as mobile phones.

[0090] Meanwhile, according to the charging power of the vehicle to be charged and the vehicle being charged in each first time interval after each power distribution or power adjustment, the corresponding remaining power supply of the power grid is updated in real time.

[0091] In addition, the power grid can be assisted by a wind-solar power generation device, and the sum of the average power and the remaining power supply of the power grid in each first time interval is determined as the final remaining power supply of the power grid.

[0092] According to the embodiments of the present invention, analyze according to the charging request and formulate a charging plan for the vehicle to be charged, including:

[0093] When the user selects the slow charging mode, determine whether the vehicle to be charged meets the slow charging conditions according to the required power of the vehicle to be charged, the vehicle parking time interval, and the rated slow charging power;

[0094] If so, determine the slow charging time interval according to the remaining power supply of the power grid and the vehicle parking time interval, and formulate a slow charging plan in combination with the rated slow charging power;

[0095] If not, ask the user whether to perform fast charging;

[0096] When the user selects the fast charging mode, calculate the power supply score for each first time interval according to the remaining power supply of the power grid, the maximum fast charging power of the vehicle to be charged, and the electricity price;

[0097] One or more first time intervals are determined as the fast charging time intervals of the vehicle to be charged in the order from the largest to the smallest power supply score, and the fast charging power of each fast charging time interval is determined according to the remaining power of the vehicle at the start time of the fast charging time interval, and a fast charging plan is formulated.

[0098] It should be noted that when the user selects the slow charging mode, it is judged whether the product of the time length of the vehicle parking time interval, the rated slow charging power and the system setting influence coefficient is greater than the power required by the vehicle to determine whether the vehicle to be charged meets the slow charging condition. When the product is greater than the power required by the vehicle, the vehicle to be charged meets the slow charging condition. According to the magnitude relationship between the remaining power supply power of the power grid in each first time interval within the vehicle parking time interval and the rated slow charging power of the vehicle to be charged, one or more first time intervals are selected and determined as the slow charging time intervals of the vehicle to be charged. When the user selects fast charging, the slow charging mode is switched to the fast charging mode.

[0099] When the user selects the fast charging mode, calculate the power difference between the remaining power supply power of the power grid in each first time interval and the maximum fast charging power of the vehicle to be charged, multiply the power difference and the electricity price in each first time interval by the corresponding influence weights respectively, accumulate the calculation results, and determine the power supply score of each first time interval. Among them, the influence weights of the power difference and the electricity price in the first time interval are both set by the system, and the sum of the influence weights of the power difference and the electricity price in the first time interval is 1. Analyze each first time interval in turn in the order from the largest to the smallest power supply score, and determine the first time interval with the remaining power supply power of the power grid greater than the minimum fast charging power of the vehicle to be charged as the fast charging time interval of the vehicle to be charged. Finally, determine the fast charging power of the current fast charging time interval as the maximum fast charging power corresponding to the remaining power of the vehicle and the remaining power supply power of the power grid.

[0100] According to the embodiment of the present invention, determining the slow charging time interval according to the remaining power supply power of the power grid and the vehicle parking time interval includes:

[0101] Filter the first time intervals with the remaining power supply power of the power grid less than the rated slow charging power of the vehicle to be charged, and determine one or more sets of first time interval sets according to the continuous first time intervals;

[0102] Divide one or more sets of first time interval sets according to the electricity price adjustment time to determine one or more sets of second time interval sets;

[0103] Calculate the first charging score of each second time interval set based on the time length and electricity price of the time interval set;

[0104] Determine the charging time required by the vehicle according to the ratio of the power required by the vehicle to the rated slow charging power;

[0105] Accumulate the time lengths of the second time interval sets in descending order of the first charging score. When the accumulated time length is greater than or equal to the required charging time of the vehicle, intercept the last second time interval set participating in the accumulation according to the first time difference between the accumulated time length and the required charging time of the vehicle, and determine the slow charging time interval as the first time interval within the second time interval set participating in the accumulation.

[0106] It should be noted that the battery temperature change of the vehicle battery during slow charging is relatively low, which has little impact on battery health. Therefore, when the vehicle is charged slowly, it is preferred to select a time interval set with a longer time length for charging. Multiply the time length and electricity price of the second time interval set by the corresponding influence weights respectively, and accumulate the calculation results to determine the first charging score of each second time interval set.

[0107] Among them, the influence weights of the time length and electricity price of the second time interval set are both set by the system, and the sum of the influence weights of the time length and electricity price of the second time interval set is 1. In order to reduce the charging cost of users, the influence weight of the electricity price is greater than the influence weight of the time length.

[0108] According to the embodiments of the present invention, determine one or more first time intervals as the fast charging time intervals of the vehicle to be charged in descending order of the power supply score, and determine the fast charging power of each fast charging time interval according to the remaining power of the vehicle at the start time of the fast charging time interval, and formulate a fast charging plan, including:

[0109] Filter the first time intervals with a power supply score less than the preset score threshold;

[0110] Determine the first first time interval as the second time interval in chronological order;

[0111] Determine the minimum power among the remaining power supply of the power grid within the second time interval and the maximum fast charging power of the vehicle to be charged as the first charging power of the second time interval;

[0112] Calculate the charging amount of the second time interval. When the charging amount of the second time interval is greater than or equal to the required power of the vehicle, determine the second time interval as the fast charging time interval and determine the first charging power as the fast charging power of the corresponding fast charging time interval;

[0113] When the charging amount of the second time interval is less than the required power of the vehicle, predict the battery temperature data at the end time of the second time interval according to the first charging power, time length and soc value of the vehicle battery at the start time of the second time interval;

[0114] When the battery temperature data is less than the first preset battery temperature threshold, the next first time interval is determined as the next second time interval in chronological order, and the first charging power of the next second time interval is determined;

[0115] When the battery temperature data is greater than or equal to the first preset battery temperature threshold, the cooling time interval for the battery temperature data to drop to the second preset battery temperature threshold is predicted based on the external environment data, the first time interval after the cooling time interval is determined as the next second time interval, and the first charging power of the next second time interval is determined;

[0116] The charging amounts of all second time intervals are accumulated. When the accumulated charging amount is greater than or equal to the power required by the vehicle, all second time intervals are determined as fast charging time intervals, and the first charging power of each second time interval is determined as the fast charging power corresponding to the fast charging time interval.

[0117] It should be noted that the first time intervals are screened based on the power supply score, and the first time intervals corresponding to the peak period electricity price are filtered through a preset score threshold. When the vehicle parking time of the vehicle to be charged includes three electricity price periods of valley, flat, and peak, the first time intervals are analyzed in the order of valley period - flat period - peak period by setting the preset score threshold twice. Among them, the preset score threshold is set and adjusted by the system according to the electricity price.

[0118] The charging amount of the second time interval is determined by the product of the time length of the second time interval and the first charging power. After the second time interval is determined as the fast charging time interval, the remaining grid power supply of the second time interval is updated according to the difference between the remaining grid power supply and the first charging power.

[0119] The second time intervals are selected for analysis in turn until the sum of the charging amounts of all fast charging time intervals is greater than the power required by the vehicle to be charged, and all fast charging time intervals and the corresponding fast charging powers of the vehicle to be charged are determined. When the charging amount of the second time interval is less than the power required by the vehicle, it is analyzed through a preset vehicle battery charging temperature prediction model to determine the battery temperature data at the end time of the second time interval. When the battery temperature data is less than the first preset battery temperature threshold, the next first time interval is determined as the next second time interval in chronological order, and the fast charging power of this second time interval is determined; otherwise, wait for the vehicle battery temperature to drop to the second preset battery temperature threshold and then select the next second time interval for analysis.

[0120] Among them, the preset vehicle battery charging temperature is obtained by training various charging data (including charging duration, charging power, battery temperature, and external environment data, etc.) generated during the vehicle charging process. The first preset battery temperature threshold and the second preset battery temperature threshold are set by those skilled in the art according to actual needs, and the first preset battery temperature threshold is greater than the second preset battery temperature threshold.

[0121] In addition, when there is no first time interval with a power supply score greater than the preset score threshold, the first time interval with the largest power supply score is selected from the filtered first time intervals and determined as the second time interval for further analysis.

[0122] According to the embodiment of the present invention, when the user selects the slow charging mode, multiple power adjustment data are determined according to the number of vehicles being charged in each first time interval, and a charging adjustment scheme is determined by analyzing the multiple power adjustment data, including:

[0123] Calculate the first adjustment score for each first time interval according to the rated slow charging power of the vehicle to be charged, the power of the remaining power of the power grid, and the electricity price;

[0124] Determine the first time intervals with the first adjustment score greater than the preset adjustment score threshold as the third time intervals;

[0125] Determine multiple power adjustment data according to the number of vehicles being charged in each third time interval; each power adjustment data corresponds to the slow charging time interval and the rated slow charging power of a vehicle being charged;

[0126] Calculate the second adjustment score for each power adjustment data;

[0127] Select the power adjustment data for analysis in order from largest to smallest according to the second adjustment score, and obtain the time position of the slow charging time interval of the vehicle being charged corresponding to the power adjustment data in the set of corresponding first time intervals;

[0128] When the slow charging time interval of the vehicle being charged corresponding to the power adjustment data is at both ends of the set of corresponding first time intervals, the power adjustment data meets the adjustment conditions;

[0129] On the contrary, according to the slow charging time interval of the vehicle being charged corresponding to the power adjustment data, the set of corresponding first time intervals is divided, and it is judged whether the time lengths of the two sub-time interval sets obtained after the division are both greater than the preset time length threshold;

[0130] If so, the power adjustment data meets the adjustment conditions; if not, it does not meet the adjustment conditions, and the power adjustment data is filtered;

[0131] When the power adjustment data meets the adjustment conditions, adjust the slow charging time interval of the vehicle corresponding to the power adjustment data to the first time interval connected to the end of the corresponding first time interval set, and determine the third time interval corresponding to the power adjustment data as the slow charging time interval of the vehicle to be charged.

[0132] It should be noted that the first adjustment score m of the first time interval 1 The calculation method is expressed by the formula ;

[0133] where p a(L1) is the rated slow charging power of the vehicle to be charged, p RP is the remaining power supply of the power grid, q EP is the electricity price, k a and k b are both influence weights. The values of the influence weights k a and k b are set by the system, and k a +k b = 1.

[0134] Among them, the preset adjustment score threshold and the preset time length threshold are set by those skilled in the art according to actual needs.

[0135] In addition, when the remaining power supply of the power grid in the first time interval connected to the end of the corresponding first time interval set is less than the slow charging power of the slow charging time interval, analyze each first time interval connected end to end in the first time interval set in turn, and determine the first time interval in which the remaining power supply of the power grid is greater than the slow charging power of the slow charging time interval as the slow charging time interval of the vehicle after adjustment in the power adjustment data.

[0136] According to the embodiment of the present invention, it further includes:

[0137] The calculation method of the second adjustment score m 2 is expressed by the formula: ;

[0138] where m 1 is the first adjustment score, p b(L1) is the rated slow charging power of the vehicle corresponding to the power adjustment data being charged, p 0 is the system preset supplementary power, p RP is the remaining power supply of the power grid in the first time interval, k 1 is the adjustment coefficient of the second adjustment score.

[0139] It should be noted that the adjustment coefficient k of the second adjustment score 1Set by the system to avoid the situation where after adjusting the rated slow charging power of the vehicle being charged within the current first time interval, the remaining power supply of the power grid does not meet the rated slow charging power of the vehicle to be charged, that is, the sum of the rated slow charging power of the vehicle being charged and the remaining power supply of the power grid is less than the rated slow charging power of the vehicle to be charged. When calculating the second adjustment score m 2 add the system preset supplementary power p preset by the system 0 .

[0140] According to the embodiments of the present invention, when the user selects the fast charging mode, calculate the third adjustment score for each first time interval, and analyze each first time interval in order from largest to smallest according to the third adjustment score to determine the charging adjustment plan, including:

[0141] Calculate the third adjustment score for each first time interval according to the minimum fast charging power of the vehicle to be charged, the remaining power supply of the power grid in the first time interval, and the minimum time interval between the first time interval and the occupied time interval;

[0142] Determine the first time interval with the largest third adjustment score as the fourth time interval;

[0143] Calculate the second time difference between the fourth time interval and the previous occupied time interval of the vehicle to be charged, and calculate the third time difference between the fourth time interval and the next occupied time interval of the vehicle to be charged;

[0144] Predict the battery temperature data at the start time of the fourth time interval according to the battery temperature data, external environment data at the end time of the previous occupied time interval, and the second time difference;

[0145] According to the first preset battery temperature threshold and the fast charging power in the next occupied time interval, calculate the maximum battery temperature data at the start time of the next occupied time interval, and predict the maximum battery temperature data at the end time of the fourth time interval in combination with the third time difference;

[0146] Analyze according to the battery temperature data at the start time of the fourth time interval and the maximum battery temperature data at the end time to determine the first predicted charging power of the vehicle to be charged within the fourth time interval;

[0147] When the first predicted charging power is greater than the minimum fast charging power of the vehicle to be charged and less than the sum of the remaining power supply of the power grid and the maximum fast charging power of the vehicle being charged within the fourth time interval, the fourth time interval meets the adjustment condition;

[0148] Determine the vehicle being charged corresponding to the minimum fast charging power greater than the difference between the first predicted charging power and the remaining power supply of the power grid as the adjusted vehicle;

[0149] Adjust the fast charging time interval of the vehicle according to the remaining fast charging power of the power grid in other first time intervals; determine the fourth time interval as the fast charging power interval of the vehicle to be charged, and determine the first predicted charging power as the corresponding fast charging power;

[0150] When the fourth time interval does not meet the adjustment condition, determine the next first time interval as the fourth time interval in the order from largest to smallest third adjustment score, and perform adjustment verification again.

[0151] It should be noted that the third adjustment score m of the first time interval 3 The calculation method is expressed by the formula ;

[0152] Among them, p a(L2)min is the minimum fast charging power of the vehicle to be charged, p RP is the remaining power supply of the power grid in the first time interval, T a is the minimum time interval between the first time interval and the occupied time interval, k c and k d are both influence weights. The values of the influence weights k c and k d are set by the system, and k c +k d = 1.

[0153] The second time difference is the time difference between the start time of the fourth time interval and the end time of the previous occupied time interval of the vehicle to be charged, and the third time difference is the time difference between the end time of the fourth time interval and the start time of the next occupied time interval of the vehicle to be charged. Analyze through a preset vehicle battery charging temperature prediction model, calculate the battery temperature data at the start time of the fourth time interval and the maximum battery temperature at the end time, and determine the first predicted charging power of the vehicle to be charged within the fourth time interval according to the time length of the fourth time interval. Analyze the fast charging power of each charging vehicle within the fourth time interval, determine the charging vehicle corresponding to the minimum fast charging power greater than the difference between the first predicted charging power and the remaining power supply of the power grid as the adjustment vehicle, and adjust the fast charging scheme of the adjustment vehicle within the fourth time interval to other first time intervals where the remaining power supply of the power grid is greater than the fast charging power of the adjustment vehicle within the fourth time interval.

[0154] According to the embodiments of the present invention, it further includes:

[0155] When the power adjustment condition of the fast charging mode is still not met after all first time intervals are analyzed, calculate the fourth adjustment score of each fast charging time interval according to the maximum fast charging power of the vehicle to be charged, the fast charging power of the fast charging time interval, and the remaining power supply of the power grid;

[0156] Determine the fast charging time interval with the largest fourth adjustment score as the fifth time interval;

[0157] Predict the maximum battery temperature data at the end of the fifth time interval based on the fourth time difference between the fifth time interval and the next fast charging time interval of the vehicle to be charged and the maximum battery temperature data at the start time of the next fast charging time interval;

[0158] Analyze based on the battery temperature data at the start time of the fifth time interval and the maximum battery temperature data at the end time to determine the second predicted charging power of the vehicle to be charged within the fifth time interval;

[0159] Determine the charging vehicle corresponding to the minimum fast charging power greater than the difference between the second predicted charging power and the fast charging power of the vehicle to be charged within the fifth time interval as the adjustment vehicle;

[0160] Update the fast charging power of the vehicle to be charged within the fifth time interval according to the second predicted charging power.

[0161] It should be noted that when the analysis of all the first time intervals is completed, if the charging amount in the fast charging time interval of the vehicle to be charged is still less than the required power of the vehicle to be charged, it is determined that the power adjustment condition for the fast charging mode is still not met, and the fourth adjustment score m of the fast charging time interval n is calculated 4(n) 。 ;

[0162] Among them, p a(L2)max is the maximum fast charging power of the vehicle to be charged, p a(L2)n is the fast charging power of the vehicle to be charged in the fast charging time interval n, p RP(n) is the remaining power supply of the power grid in the fast charging time interval n, k e and k f are both influence weights. The influence weights k e and k f are set by the system, and k e +k f = 1.

[0163] Through analysis by a preset vehicle battery charging temperature prediction model, calculate the battery temperature data at the start time of the fifth time interval and the maximum battery temperature data at the end time, determine the second predicted charging power of the vehicle to be charged within the fifth time interval. When the second predicted charging power is greater than the maximum fast charging power of the vehicle to be charged, determine the maximum fast charging power of the vehicle to be charged as the second predicted charging power. After determining the adjustment vehicle, adjust the fast charging plan of the adjustment vehicle within the fifth time interval to other first time intervals where the remaining power supply of the other power grid is greater than the fast charging power of the adjustment vehicle within the fifth time interval.

[0164] According to an embodiment of the present invention, it further includes:

[0165] Input the required power of the vehicle being charged and the vehicle parking time interval into a preset vehicle charging cost prediction model, and analyze in combination with the required power of other vehicles being charged and the vehicle parking time interval to determine the maximum charging cost of the vehicle being charged;

[0166] Calculate the predicted charging cost of the vehicle being charged according to the charging time interval, charging power and electricity price of the vehicle being charged;

[0167] When the predicted charging cost is greater than the maximum charging cost, a prohibition adjustment mark is made on the vehicle being charged.

[0168] It should be noted that when the vehicle selects to charge, the required power of the vehicle being charged and the vehicle parking time interval are analyzed through a preset vehicle charging cost prediction model, and analyzed in combination with the required power of other vehicles being charged and the vehicle parking time interval to determine the maximum charging amount and minimum charging amount of the vehicle being charged during the peak, valley and flat electricity price periods. The maximum charging cost of the vehicle being charged is calculated in combination with the electricity prices during the peak, valley and flat electricity price periods. The predicted charging cost of each vehicle being charged is calculated in real time. When the predicted charging cost is greater than the corresponding maximum charging cost, a prohibition adjustment mark is made on the vehicle being charged and it no longer participates in the subsequent adjustment of the charging time interval.

[0169] The preset vehicle charging cost prediction model is trained by parameters such as the parking time interval, charging amount, charging cost, average number of charging vehicles per day at the charging station, average charging cost and average charging unit price of each vehicle in the vehicle historical charging data.

[0170] Figure 2 The block diagram of a charging strategy optimization system based on big data provided by the present invention is shown.

[0171] As Figure 2 shown, a second aspect of the present invention provides a charging strategy optimization system based on big data, including:

[0172] A data acquisition module, configured to acquire charging request data of a vehicle to be charged; the charging request data includes the charging mode selected by the user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode;

[0173] A time interval division module, configured to divide the vehicle parking time interval into multiple first time intervals based on a preset time interval;

[0174] A charging plan formulation module, which is used to analyze according to a charging request, formulate a charging plan for a vehicle to be charged, and charge the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan;

[0175] A charging plan adjustment module, which is used to analyze according to the selected charging mode when the charging plan of the vehicle to be charged does not meet the vehicle charging conditions. When the user selects the slow charging mode, determine a plurality of power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the plurality of power adjustment data to determine a charging adjustment plan; when the user selects the fast charging mode, calculate the third adjustment score of each first time interval, and analyze each first time interval in turn according to the order from large to small of the third adjustment score to determine a charging adjustment plan;

[0176] A remaining grid power supply monitoring module, which is used to adjust the charging plans of the vehicle to be charged and the vehicles being charged according to the charging adjustment plan, and update the remaining grid power supply in the corresponding first time interval.

[0177] The information involved in this application (including but not limited to user device information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.), and signals (including but not limited to signals transmitted between user terminals and other devices, etc.) are all authorized by users or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards of relevant countries and regions. For example, the "charging request data of the vehicle to be charged" and "remaining grid power supply" involved in this disclosure are all obtained under full authorization.

[0178] The present invention discloses a charging strategy optimization method and system based on big data. The method includes: dividing the vehicle parking time interval into a plurality of first time intervals based on a preset time interval; analyzing according to a charging request to formulate a charging plan for a vehicle to be charged; when the charging plan of the vehicle to be charged does not meet the vehicle charging conditions, in the slow charging mode, determine a plurality of power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the plurality of power adjustment data to determine a charging adjustment plan; in the fast charging mode, calculate the third adjustment score of each first time interval, and analyze each first time interval in turn according to the order from large to small of the third adjustment score to determine a charging adjustment plan; update the remaining grid power supply. The present invention optimizes the charging load by reasonably arranging the charging time period, reduces the grid pressure, and improves the stability and safety of the grid operation.

[0179] In several embodiments provided by this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed with each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0180] In each embodiment of the present invention, each functional unit can be all integrated in a processing unit, or each unit can be separately used as a unit alone, or two or more units can be integrated in one unit; the above-mentioned integrated unit can be implemented in the form of hardware, or can be implemented in the form of hardware plus software functional units.

[0181] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the foregoing storage medium includes: removable storage devices, read-only memories, random access memories, magnetic disks, or optical disks and other various media that can store program codes.

[0182] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device to execute all or part of the methods described in the various embodiments of the present invention. And the foregoing storage medium includes: removable storage devices, ROM, RAM, magnetic disks, or optical disks and other various media that can store program codes.

Claims

1. A charging strategy optimization method based on big data, characterized in that: include: Obtaining charging request data of the vehicle to be charged; the charging request data includes the charging mode selected by the user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode; Dividing the vehicle parking time interval into a plurality of first time intervals based on a preset time interval; Analyze the charging request, formulate a charging plan for the vehicle to be charged, and charge the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan; When the charging scheme of the vehicle to be charged does not meet the vehicle charging condition, an analysis is performed according to the charging mode selected by the user. When the user selects the slow charging mode, a plurality of power adjustment data are determined according to the number of vehicles being charged in each first time interval, and the charging adjustment scheme is determined by analyzing the plurality of power adjustment data; When the user selects the fast charging mode, the third adjustment score of each first time interval is calculated, and each first time interval is analyzed in descending order of the third adjustment score to determine a charging adjustment plan; Adjusting the charging schemes of the vehicle to be charged and the vehicle being charged according to the charging adjustment scheme, and updating the remaining power supply power of the power grid corresponding to the first time interval; When the user selects the slow charging mode, a plurality of power adjustment data are determined according to the number of vehicles being charged in each first time interval, and a charging adjustment scheme is determined by analyzing the plurality of power adjustment data, including: Calculate a first adjustment score for each first time interval according to the rated slow charging power of the vehicle to be charged, the power of the remaining power of the power grid, and the electricity price; Determine a first time interval in which the first adjustment score is greater than a preset adjustment score threshold as a third time interval; Determine a plurality of power adjustment data according to the number of vehicles being charged in each third time interval; each power adjustment data corresponds to a slow charging time interval and a rated slow charging power of a vehicle being charged; Calculating a second adjustment score for each power adjustment data; Select the power adjustment data in descending order of the second adjustment scores for analysis, and obtain the time position of the slow charging time interval of the vehicle being charged corresponding to the power adjustment data in the corresponding first time interval set; When the slow charging time interval of the vehicle being charged corresponding to the power adjustment data is at both ends of the corresponding first time interval set, the power adjustment data meets the adjustment condition; On the contrary, the corresponding first time interval set is divided according to the slow charging time interval of the vehicle being charged corresponding to the power adjustment data, and it is determined whether the time lengths of the two sub-time interval sets obtained after the division are both greater than the preset time length threshold; If yes, the power adjustment data meets the adjustment condition; if no, the adjustment condition is not met, and the power adjustment data is filtered; When the power adjustment data meets the adjustment condition, the slow charging time interval of the vehicle being charged corresponding to the power adjustment data is adjusted to the first time interval connected to the end of the corresponding first time interval set, and the third time interval corresponding to the power adjustment data is determined as the slow charging time interval of the vehicle to be charged; The calculation method of the second adjustment score m2 is expressed by the formula: ； Among them, m1 is the first adjustment score, p L1 The power adjustment data corresponds to the rated slow charging power of the vehicle being charged, p0 is the system preset supplementary power, and p RP is the remaining power supply power of the power grid, and k1 is the adjustment coefficient of the second adjustment score.

2. The charging strategy optimization method based on big data according to claim 1 is characterized in that: The step of analyzing the charging request and formulating a charging plan for the vehicle to be charged includes: When the user selects the slow charging mode, it is determined whether the vehicle to be charged meets the slow charging conditions according to the required power of the vehicle to be charged, the vehicle parking time interval and the rated slow charging power; If so, the slow charging time interval is determined according to the remaining power supply of the power grid and the parking time interval of the vehicle, and a slow charging plan is formulated in combination with the rated slow charging power; If not, the user is asked whether to perform fast charging; When the user selects the fast charging mode, the power supply score of each first time interval is calculated according to the remaining power supply power of the power grid, the maximum fast charging power of the vehicle to be charged and the electricity price; One or more first time intervals are determined as fast charging time intervals for the vehicle to be charged in descending order of the power supply scores, and the fast charging power of each fast charging time interval is determined according to the remaining power of the vehicle at the start time of the fast charging time interval, and a fast charging plan is formulated.

3. The charging strategy optimization method based on big data according to claim 2 is characterized in that: The determining of the slow charging time interval according to the remaining power supply of the power grid and the parking time interval of the vehicle includes: Filtering the first time intervals in which the remaining power supply power of the power grid is less than the rated slow charging power of the vehicle to be charged, and determining one or more sets of first time intervals according to the continuous first time intervals; Dividing the one or more sets of first time intervals according to the electricity price adjustment time to determine one or more sets of second time intervals; Calculate a first charging score for each second time interval set based on the time length and electricity price of the time interval set; Determine the required charging time for the vehicle based on the ratio of the required power of the vehicle and the rated slow charging power; The time lengths of the second time interval set are accumulated in descending order of the first charging scores. When the accumulated time length is greater than or equal to the charging time required for the vehicle, the second time interval set last accumulated is intercepted according to the first time difference between the accumulated time length and the charging time required for the vehicle, and the first time interval in the accumulated second time interval set is determined as the slow charging time interval.

4. The charging strategy optimization method based on big data according to claim 2 is characterized in that: The method of determining one or more first time intervals as the fast charging time intervals of the vehicle to be charged in descending order of the power supply scores, and determining the fast charging power of each fast charging time interval according to the remaining power of the vehicle at the start time of the fast charging time interval, and formulating a fast charging plan includes: Filtering the first time interval in which the power supply score is less than a preset score threshold; Determine the first time interval as the second time interval in chronological order; Determine the minimum power between the remaining power supply power of the power grid in the second time interval and the maximum fast charging power of the vehicle to be charged as the first charging power in the second time interval; Calculating the charge amount in the second time interval, and when the charge amount in the second time interval is greater than or equal to the power required by the vehicle, determining the second time interval as a fast charging time interval, and determining the first charging power as the fast charging power corresponding to the fast charging time interval; When the charge amount in the second time interval is less than the amount of electricity required by the vehicle, predicting the battery temperature data at the end time of the second time interval according to the first charging power, time length and the vehicle battery soc value at the start time of the second time interval; When the battery temperature data is less than a first preset battery temperature threshold, determining the next first time interval as the next second time interval in chronological order, and determining the first charging power of the next second time interval; When the battery temperature data is greater than or equal to a first preset battery temperature threshold, predicting a cooling time interval in which the battery temperature data is reduced to a second preset battery temperature threshold according to the external environment data, determining the first first time interval after the cooling time interval as the next second time interval, and determining the first charging power for the next second time interval; The charging amounts of all the second time intervals are accumulated. When the accumulated charging amounts are greater than or equal to the amount of electricity required by the vehicle, all the second time intervals are determined as fast charging time intervals, and the first charging power of each second time interval is determined as the fast charging power of the corresponding fast charging time interval.

5. The charging strategy optimization method based on big data according to claim 1 is characterized in that: When the user selects the fast charging mode, the third adjustment score of each first time interval is calculated, and each first time interval is analyzed in descending order of the third adjustment score to determine the charging adjustment plan, including: Calculate a third adjustment score for each first time interval according to the minimum fast charging power of the vehicle to be charged, the remaining power supply power of the power grid in the first time interval, and the minimum time interval between the first time interval and the occupied time interval; determining the first time interval with the largest third adjustment score as the fourth time interval; Calculating a second time difference between the fourth time interval and a previous occupied time interval of the vehicle to be charged, and calculating a third time difference between the fourth time interval and a next occupied time interval of the vehicle to be charged; Predicting the battery temperature data at the start time of the fourth time interval based on the battery temperature data at the end time of the previous occupied time interval, the external environment data, and the second time difference; Calculate the maximum battery temperature data at the start time of the next occupied time interval according to the first preset battery temperature threshold and the fast charging power of the next occupied time interval, and predict the maximum battery temperature data at the end time of the fourth time interval in combination with the third time difference; Determine a first predicted charging power for the vehicle to be charged in the fourth time interval by analyzing the battery temperature data at the start time of the fourth time interval and the maximum battery temperature data at the end time; When the first predicted charging power is greater than the minimum fast charging power of the vehicle to be charged and less than the sum of the remaining power supply of the power grid and the maximum fast charging power of the vehicle being charged in the fourth time interval, the fourth time interval meets the adjustment condition; Determine the charging vehicle corresponding to the minimum fast charging power value that is greater than the difference between the first predicted charging power and the remaining power supply power of the power grid as an adjustment vehicle; The fast charging time interval of the adjusted vehicle is adjusted according to the remaining fast charging power of the power grid in other first time intervals; the fourth time interval is determined as the fast charging power interval of the vehicle to be charged, and the first predicted charging power is determined as the corresponding fast charging power; When the fourth time interval does not meet the adjustment condition, the next first time interval is determined as the fourth time interval in descending order of the third adjustment scores, and the adjustment verification is performed again.

6. The charging strategy optimization method based on big data according to claim 5 is characterized in that: Also includes: When the power adjustment condition of the fast charging mode is still not met after all the first time intervals are analyzed, a fourth adjustment score for each fast charging time interval is calculated according to the maximum fast charging power of the vehicle to be charged, the fast charging power of the fast charging time interval, and the remaining power supply power of the power grid; The fast charging time interval with the largest fourth adjustment score is determined as the fifth time interval; Predicting the maximum battery temperature data at the end time of the fifth time interval according to the fourth time difference between the fifth time interval and the next fast charging time interval of the vehicle to be charged and the maximum battery temperature data at the start time of the next fast charging time interval; Analyze the battery temperature data at the start time of the fifth time interval and the maximum battery temperature data at the end time to determine a second predicted charging power for the vehicle to be charged in the fifth time interval; Determine the vehicle being charged, which corresponds to the minimum fast charging power value greater than the difference between the second predicted charging power and the fast charging power of the vehicle to be charged in the fifth time interval, as an adjustment vehicle; The fast charging power of the vehicle to be charged in the fifth time interval is updated according to the second predicted charging power.

7. The charging strategy optimization method based on big data according to claim 1 is characterized in that: Also includes: The required power and parking time interval of the vehicle being charged are input into a preset vehicle charging cost prediction model, and the required power and parking time interval of other vehicles being charged are analyzed to determine the maximum charging cost of the vehicle being charged; Calculate the predicted charging cost of the vehicle being charged according to the charging time interval, charging power and electricity price of the vehicle being charged; When the predicted charging fee is greater than the maximum charging fee, a prohibition adjustment mark is set for the charging vehicle.

8. A charging strategy optimization system based on big data, used to implement the charging strategy optimization method based on big data as described in any one of claims 1 to 7, characterized in that: include: A data acquisition module, used to acquire charging request data of a vehicle to be charged; The charging request data includes the charging mode selected by the user, the required power of the vehicle to be charged, the vehicle parking time interval, the rated fast charging power interval and the rated slow charging power; the charging mode includes a slow charging mode and a fast charging mode; A time interval division module, used to divide the vehicle parking time interval into a plurality of first time intervals based on a preset time interval; A charging plan formulation module, used to analyze the charging request, formulate a charging plan for the vehicle to be charged, and charge the vehicle to be charged according to the charging plan; the charging plan includes a fast charging plan and a slow charging plan; A charging scheme adjustment module, configured to analyze the charging mode selected by the user when the charging scheme of the vehicle to be charged does not meet the vehicle charging conditions, and when the user selects the slow charging mode, determine a plurality of power adjustment data according to the number of vehicles being charged in each first time interval, and analyze the plurality of power adjustment data to determine the charging adjustment scheme; When the user selects the fast charging mode, the third adjustment score of each first time interval is calculated, and each first time interval is analyzed in descending order of the third adjustment score to determine a charging adjustment plan; The grid surplus power monitoring module is used to adjust the charging schemes of the vehicle to be charged and the vehicle being charged according to the charging adjustment scheme, and to update the grid surplus power corresponding to the first time interval.

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