A new energy charging station optimization scheduling method, system, equipment and medium

Abstract

The present invention discloses an optimization scheduling method, system, equipment and medium for a new energy charging station, and relates to the technical field of charging pile scheduling optimization, comprising the following steps: setting a vehicle data acquisition terminal at the entrance of the charging station to collect real-time data of the vehicle; acquiring the charging power of the vehicle battery based on the real-time data of the vehicle; analyzing the fluctuation index of the idle charging pile; matching the best idle charging pile for the vehicle or adopting different charging strategies based on the fluctuation index of the idle charging pile and the real-time data of the vehicle; guiding the vehicle to the corresponding charging pile for charging through a guide indicator light; the present invention is used to solve the problem that the existing charging pile scheduling optimization technology still has insufficient consideration of the stability of the charging pile, resulting in a large deviation between the charging time of the vehicle and the expectation and a shortened life of the battery pack of the vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile scheduling optimization, and specifically to an optimization scheduling method, system, equipment and medium for a new energy charging station. Background Art

[0002] Charging pile scheduling optimization technology refers to the use of algorithms, data analysis and intelligent methods to effectively schedule and manage new energy charging piles in order to improve charging efficiency, optimize resource utilization, reduce user waiting time, balance grid load and improve user experience. The goal of charging pile scheduling optimization technology is to meet charging needs to the greatest extent possible by reasonably arranging parameters such as the order of use of charging piles, charging time and charging power, so as to improve the operating efficiency and service quality of charging stations. This technology usually combines real-time data collection, predictive analysis, optimization algorithms and intelligent control methods to provide a scientific basis for scheduling decisions of charging piles.

[0003] Existing charging pile scheduling optimization technology usually allocates fast charging piles or slow charging piles to vehicles based on factors such as the vehicle's charging power and charging time. At the same time, the optimal fast charging pile is allocated based on the rated power of the fast charging pile and the vehicle's charging power to ensure fast charging of the vehicle and save charging resources. However, different charging piles are affected by various factors such as long-term use and the environment, and their internal stability varies. The difference in stability will cause the charging power to fluctuate, further causing the vehicle's charging time to deviate greatly from expectations, and using a charging pile with poor stability to charge the vehicle will also damage the life of the vehicle's battery pack. For example, in the publication number C The patent application N112150037A discloses a charging station and a charging pile scheduling method in the charging station. The scheme schedules the charging piles by analyzing the utilization rate of the charging station and other factors that affect the life of the charging piles, but ignores the user's experience. The charging piles have a rated power. As long as the power does not exceed the rated power, long-term use has little effect on the life of the charging piles. The scheduling of the charging piles should effectively consider the user's experience, charging efficiency and charging cost. The existing charging pile scheduling optimization technology still has insufficient consideration of the stability of the charging piles, resulting in a large deviation between the charging time of the vehicle and the expectation and a reduced life of the vehicle's battery pack. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the prior art to at least a certain extent, by setting a vehicle data acquisition terminal at the entrance of the charging station. When the vehicle enters the charging station, the driver scans the code to fill in the real-time data of the vehicle, and then obtains the charging power of the vehicle battery based on the real-time data of the vehicle. At the same time, the status of the charging piles in the charging station is monitored in real time, and the idle charging piles are found. The fluctuation index of the idle charging piles is analyzed, and then based on the fluctuation index of the idle charging piles and the real-time data of the vehicle, the best idle charging pile is matched for the vehicle or different charging strategies are adopted. Finally, based on the matched charging piles, the vehicle is guided to the corresponding charging pile for charging through the guide indicator light, so as to solve the problem that the existing charging pile scheduling optimization technology still has insufficient consideration of the stability of the charging piles, resulting in a large deviation between the charging time of the vehicle and the expected and a reduced life of the battery pack of the vehicle.

[0005] To achieve the above objectives, in a first aspect, the present application provides a method for optimizing and scheduling a new energy charging station, comprising the following steps:

[0006] A vehicle data collection terminal is set up at the entrance of the charging station. When a vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data;

[0007] Obtain the charging power of the vehicle battery based on the real-time data of the vehicle, monitor the status of the charging piles in the charging station in real time, and find idle charging piles;

[0008] Analyze the fluctuation index of idle charging piles;

[0009] Based on the fluctuation index of idle charging piles and real-time vehicle data, the vehicle is matched with the best idle charging pile or different charging strategies are adopted;

[0010] Based on the matching charging pile, the vehicle is guided to the corresponding charging pile for charging through the guidance indicator light.

[0011] Furthermore, a vehicle data collection terminal is set at the entrance of the charging station. When a vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data, including the following sub-steps:

[0012] The vehicle data collection terminal is a web page program;

[0013] When a vehicle enters a charging station, the driver scans a code to fill in the vehicle's real-time data, which includes battery power, vehicle brand and model, and charging mode, which includes fast charging and slow charging.

[0014] Furthermore, obtaining the charging power of the vehicle battery based on the real-time data of the vehicle, and monitoring the status of the charging piles in the charging station in real time, and searching for idle charging piles include the following sub-steps:

[0015] Get the vehicle brand and model;

[0016] Find the rated charging power and rated battery capacity corresponding to the vehicle brand and model in the power database, and mark them as charging power and battery capacity respectively;

[0017] The power database records the rated charging power and rated battery capacity of all new energy vehicles;

[0018] The status of the charging piles in the charging station is monitored, and the idle charging piles in the charging station are named idle charging piles.

[0019] Furthermore, analyzing the fluctuation index of the idle charging pile includes the following sub-steps:

[0020] Get the rated power of the idle charging pile;

[0021] Calculate the rated power minus the charging power, and mark the result as the power difference;

[0022] If the power difference of the idle charging piles is a negative number, an insufficient power signal is output; if the power difference of the idle charging piles is a non-negative number, a sufficient power signal is output;

[0023] If the output power is sufficient, the idle charging pile is marked as a pending charging pile;

[0024] The fluctuation parameters of the pending charging piles are analyzed based on their historical charging data, and the pending charging piles are sorted based on the power difference.

[0025] Furthermore, analyzing the fluctuation parameters of the pending electric piles based on the historical charging data of the pending electric piles, and sorting the pending electric piles based on the power difference includes the following sub-steps:

[0026] For any pending charging pile, obtain historical charging data of the pending charging pile, wherein the historical charging data includes historical estimated charging time and historical actual charging time;

[0027] Calculate HAT / HET and mark the calculation result as historical fluctuation, where HAT is the historical actual charging time and HET is the historical estimated charging time; count the number of different historical fluctuations and name it as the fluctuation number;

[0028] Create a histogram with historical fluctuations as the X-axis and fluctuation quantity as the Y-axis, named as fluctuation analysis histogram, and enter the historical fluctuations and the corresponding fluctuation quantity into the fluctuation analysis histogram;

[0029] Obtain the highest first analysis number of benchmarks, and name them the first benchmark, the second benchmark, and the third benchmark in ascending order according to their heights; mark the range of historical fluctuations from the first benchmark to the second benchmark as the first range; mark the range of historical fluctuations from the first benchmark to the third benchmark as the second range; mark the range of historical fluctuations from the second benchmark to the third benchmark as the third range;

[0030] Count the union of the first range, the second range and the third range, mark it as a fluctuation union, and mark the historical fluctuations and the number of fluctuations in the fluctuation union as fluctuations to be analyzed and the number to be analyzed respectively;

[0031] The number of fluctuations to be analyzed in the fluctuation set is marked as symbol n, and the fluctuation to be analyzed and the number to be analyzed corresponding to the fluctuation to be analyzed are marked as symbol W respectively. i and Q i Represents, where i is an integer and 1≤i≤n, and i is the sequence number of W and Q;

[0032] By formula Calculate the fluctuation parameter of the pending electric pile, where V is the fluctuation parameter;

[0033] Calculate V×(α×PD+1), mark the result as the fluctuation index, where PD is the power difference, α is the difference coefficient, mark the result as the fluctuation index, sort and number the pending charging piles in the order of the fluctuation index from small to large, and use the symbol P m Represents, where m is a non-zero natural number and m is the sequence number of P.

[0034] Furthermore, based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, matching the vehicle with the best idle charging pile or adopting different charging strategies includes the following sub-steps:

[0035] Get the charging mode. If the charging mode is slow charging, get the battery power and battery capacity, calculate BC-(BL×BC), and mark the calculation result as the amount to be charged, where BC is the battery capacity and BL is the battery power.

[0036] Get the rated power of the slow charging pile, named slow charging power, calculate the battery power divided by the slow charging power, and mark the calculation result as the estimated charging time;

[0037] Obtain the current time, compare the current time with the first time threshold and the second time threshold, and if the current time is within the first time threshold and the second time threshold, output a normal charging signal; otherwise, output an energy-saving charging signal;

[0038] If a normal charging signal is output, the vehicle will be charged through a slow charging pile for half of the estimated charging time. Charging will be stopped after the time is reached. At the same time, the current grid power consumption is monitored in real time to see if it is off-peak power. If so, charging will continue until the vehicle is fully charged; if not, charging will be stopped until the off-peak power is reached and then continued;

[0039] If the energy-saving charging signal is output, the slow charging pile is controlled not to charge the vehicle, and the vehicle will be charged again when the power is low;

[0040] If the charging mode is fast charging, the pending charging pile of P1 is marked as the target charging pile, and the vehicle is assigned to the target charging pile.

[0041] Furthermore, based on the matched charging pile, guiding the vehicle to the corresponding charging pile for charging by the guide indicator light includes the following sub-steps:

[0042] If the charging mode is slow charging, the vehicle will be guided to any slow charging station through the guidance indicator light;

[0043] If the charging mode is fast charging, the vehicle will be guided to the target charging station through the guidance indicator light.

[0044] In a second aspect, the present application provides an optimization scheduling system for a new energy charging station, including a vehicle data acquisition module, a state monitoring module, a fluctuation analysis module, a charging scheduling module and a vehicle guidance module; the vehicle data acquisition module, the state monitoring module, the fluctuation analysis module and the vehicle guidance module are respectively connected to the charging scheduling module data;

[0045] The vehicle data collection module is used to set a vehicle data collection terminal at the entrance of the charging station. When the vehicle enters the charging station, the driver scans the code to fill in the real-time data of the vehicle;

[0046] The state monitoring module is used to obtain the charging power of the vehicle battery based on the real-time data of the vehicle, and at the same time monitor the state of the charging piles in the charging station in real time to find idle charging piles;

[0047] The fluctuation analysis module is used to analyze the fluctuation index of the idle charging pile;

[0048] The charging scheduling module is used to match the best idle charging pile for the vehicle or adopt different charging strategies based on the fluctuation index of the idle charging pile and the real-time data of the vehicle;

[0049] The vehicle guidance module is used to guide the vehicle to the corresponding charging pile for charging through the guidance indicator light based on the matched charging pile.

[0050] In a third aspect, the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the above method are performed.

[0051] In a fourth aspect, the present application provides a storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the above method are performed.

[0052] Beneficial effects of the present invention: The present invention sets a vehicle data collection terminal at the entrance of the charging station. When the vehicle enters the charging station, the driver scans the code to fill in the real-time data of the vehicle, and then calculates the power difference of different charging piles to the vehicle based on the real-time data of the vehicle, and then analyzes the fluctuation index of the idle charging pile. Then, based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, the best idle charging pile is matched for the vehicle. The advantage is that fast charging piles usually have different rated powers, and the charging power of the vehicle has a maximum value. If the maximum value is exceeded, it will cause a waste of charging resources. At the same time, based on the historical charging data of the charging pile, the power fluctuation of the charging pile during charging is analyzed, and the charging pile with a small power difference and a small fluctuation is selected for the vehicle to charge, thereby improving the utilization rate of charging resources and the stability of the charging process;

[0053] The present invention formulates different charging strategies for vehicles that need slow charging according to the current time. When the current time is within the first time threshold and the second time threshold, the vehicle is first partially charged, and then the vehicle is charged during the low electricity consumption period; when the current time is not within the first time threshold and the second time threshold, the charging gun will not be charged when it is inserted into the vehicle, and the charging process of the vehicle needs to wait until the low electricity consumption period to start. The advantage is that vehicles that need slow charging usually do not move for a long time, and if the vehicle comes to charge within the first time threshold and the second time threshold, the vehicle may be used later due to the early time, so part of the electricity is charged to ensure the normal use of the vehicle, and then the remaining charging process is completed with low-valley electricity. If the vehicle comes to charge outside the first time threshold and the second time threshold, the vehicle usually stops all night due to the late time, and the low-valley electricity can be fully used to charge it at night, which improves the rationality of charging pile scheduling and reduces the cost of charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a functional block diagram of the system of the present invention;

[0055] Figure 2 is a schematic diagram of a vehicle data collection terminal of the present invention;

[0056] Figure 3 A fluctuation analysis bar graph of the present invention;

[0057] Figure 4 The figure is a flow chart of the steps of the method of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Example 1, please refer to Figure 1 As shown, the present application provides an optimization scheduling system for a new energy charging station, including a vehicle data acquisition module, a state monitoring module, a fluctuation analysis module, a charging scheduling module and a vehicle guidance module; the vehicle data acquisition module, the state monitoring module, the fluctuation analysis module and the vehicle guidance module are respectively connected to the charging scheduling module data;

[0060] The vehicle data collection module is used to set up a vehicle data collection terminal at the entrance of the charging station. When the vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data;

[0061] The vehicle data collection module is configured with a vehicle data collection strategy, which includes:

[0062] See also Figure 2 As shown, the vehicle data collection terminal is a web page program;

[0063] When a vehicle enters a charging station, the driver scans the code to fill in the vehicle's real-time data, which includes battery power, vehicle brand and model, and charging mode. The charging mode includes fast charging and slow charging.

[0064] In actual applications, the web page program of the vehicle data collection terminal is as follows Figure 2 As shown, if the driver has filled in the rated charging power and the rated battery capacity, there is no need to fill in the vehicle brand and model. If the rated charging power and the rated battery capacity are not filled in, the system can search for the rated charging power and the rated battery capacity of the vehicle after filling in the vehicle brand and model; in this embodiment, the battery power filled in by the driver after scanning is 40%, the vehicle brand and model is "Tesla Model 3, 2023, rear-wheel drive version", and the charging mode is fast charging; fast charging and slow charging are whether the driver expects this charging to be fast charging or slow charging.

[0065] The status monitoring module is used to obtain the charging power of the vehicle battery based on the real-time data of the vehicle, and at the same time monitor the status of the charging piles in the charging station in real time and find idle charging piles;

[0066] The condition monitoring module is configured with a condition monitoring strategy, which includes:

[0067] Get the vehicle brand and model;

[0068] Find the rated charging power and rated battery capacity corresponding to the vehicle brand and model in the power database, and mark them as charging power and battery capacity respectively;

[0069] The power database records the rated charging power and rated battery capacity of all new energy vehicles;

[0070] Monitor the status of charging piles in the charging station and name the idle charging piles in the charging station as idle charging piles;

[0071] In practical applications, some data in the power database are shown in Table 1:

[0072] Table 1 Partial data in the power database

[0073]

[0074] Among them, the rated charging power is actually the maximum charging power of the vehicle, and the user can directly fill in the rated charging power and rated battery capacity after scanning the code. If the user cannot determine the rated charging power and rated battery capacity of his own vehicle, he can choose to fill in the vehicle brand model and let the system search; the search shows that the charging power of the vehicle is 170kW, and the rated battery capacity is 60kWh; the status of the charging piles in the charging station is monitored, and the idle charging piles in the charging station are named idle charging piles, which are referred to as idle charging piles A, idle charging piles B and idle charging piles C in this embodiment.

[0075] The fluctuation analysis module is used to analyze the fluctuation index of the idle charging piles; the fluctuation analysis module includes a pending charging pile determination unit and a charging pile fluctuation analysis unit;

[0076] The pending electric pile determination unit is configured with a pending electric pile determination strategy, and the pending electric pile determination strategy includes:

[0077] Get the rated power of the idle charging pile;

[0078] Calculate the rated power minus the charging power, and mark the result as the power difference;

[0079] If the power difference of the idle charging piles is a negative number, an insufficient power signal is output; if the power difference of the idle charging piles is a non-negative number, a sufficient power signal is output;

[0080] If the output power is sufficient, the idle charging pile is marked as a pending charging pile;

[0081] Analyze the fluctuation parameters of the pending charging piles based on their historical charging data, and sort the pending charging piles based on the power difference;

[0082] In actual applications, the rated powers of idle charging pile A, idle charging pile B, and idle charging pile C are 170kW, 180kW, and 150kW, respectively, and the power differences are calculated to be 0kW, 10kW, and -20kW, respectively. The power difference between idle charging pile A and idle charging pile B is non-negative, and a sufficient power signal is output. Idle charging pile A and idle charging pile B are marked as pending charging piles. The power difference between idle charging pile C is negative, and an insufficient power signal is output. Therefore, idle charging pile C does not participate in this scheduling. The pending charging piles include pending charging pile A and pending charging pile B.

[0083] The electric pile fluctuation analysis unit is equipped with an electric pile fluctuation analysis strategy, which includes:

[0084] For any pending charging pile, obtain the historical charging data of the pending charging pile, the historical charging data includes the historical estimated charging time and the historical actual charging time;

[0085] Calculate HAT / HET and mark the calculation result as historical fluctuation, where HAT is the historical actual charging time and HET is the historical estimated charging time; count the number of different historical fluctuations and name it as the fluctuation number;

[0086] See also Figure 3 As shown, a histogram is established with historical fluctuations as the X-axis and the fluctuation quantity as the Y-axis, named as the fluctuation analysis histogram, and the historical fluctuations and the corresponding fluctuation quantity are entered into the fluctuation analysis histogram;

[0087] In actual applications, due to too much historical charging data, this embodiment will no longer display it in detail, and only directly display the final statistical results through the fluctuation analysis bar chart; for the number of fluctuations, assuming that the historical fluctuations are 1.1, 1.1 and 1.2, the number of fluctuations of 1.1 is 2, and the number of fluctuations of 1.2 is 1; by calculating the historical fluctuations and counting the fluctuations, a fluctuation analysis bar chart is constructed as shown in FIG. Figure 3 As shown in the figure, limited by the maximum charging power of the vehicle, the calculation result of the historical fluctuation is at least 1. Figure 3 Shown is a fluctuation analysis bar chart of the pending electric pile A;

[0088] Obtain the highest first analysis number of benchmarks, and name them the first benchmark, the second benchmark, and the third benchmark in ascending order according to their heights; mark the range of historical fluctuations from the first benchmark to the second benchmark as the first range; mark the range of historical fluctuations from the first benchmark to the third benchmark as the second range; mark the range of historical fluctuations from the second benchmark to the third benchmark as the third range;

[0089] Count the union of the first range, the second range and the third range, mark it as a fluctuation union, and mark the historical fluctuations and the number of fluctuations in the fluctuation union as fluctuations to be analyzed and the number to be analyzed respectively;

[0090] In practical applications, the first analysis quantity is set to find the area with the most historical fluctuations for analysis. Usually, the fluctuation analysis bar chart is Figure 3 The same, there are some very small values, such data are usually very rare cases, so after removing them for analysis can better fit the fluctuation of the pending electric piles in most cases. The first analysis quantity is usually at least 3, and the maximum is half of the number of reference columns in the fluctuation analysis bar chart. In this embodiment, the first analysis quantity is set to 3, and the first reference column is 136, the second reference column is 142, and the third reference column is 158. The union of their ranges is the range formed by the first reference column and the second reference column, that is, the fluctuation union is (1.11, 1.12, 1.15, 1.16), and the historical fluctuations and the number of fluctuations in the fluctuation union are marked as fluctuations to be analyzed and the number to be analyzed, that is, 1.11, 1.12, 1.15 and 1.16 are marked as fluctuations to be analyzed, and the corresponding numbers to be analyzed are 136, 123, 158 and 142 respectively;

[0091] The number of fluctuations to be analyzed in the fluctuation set is marked as symbol n, and the fluctuation to be analyzed and the number to be analyzed corresponding to the fluctuation to be analyzed are marked as symbol W respectively. i and Q i Represents, where i is an integer and 1≤i≤n, and i is the sequence number of W and Q;

[0092] By formula Calculate the fluctuation parameter of the pending electric pile, where V is the fluctuation parameter;

[0093] Calculate V×(α×PD+1), and mark the result as the fluctuation index, where PD is the power difference and α is the difference coefficient. Sort and number the pending charging piles in ascending order of the fluctuation index, and use the symbol P m Indicates, where m is a non-zero natural number and m is the serial number of P;

[0094] In practical applications, the number of fluctuations to be analyzed that fluctuate and concentrate is 4, that is, n=4, among which W1 is 1.11, W2 is 1.12, W3 is 1.15, W4 is 1.16, Q1 is 136, Q2 is 123, Q3 is 158, and Q4 is 142. The fluctuation parameter V=1.14 is obtained by calculation, and the calculation result is retained to two decimal places; α is set to balance the influence of the fluctuation parameter and the power difference on the fluctuation index. Under normal circumstances, the rated power of the charging pile assigned to the vehicle exceeds the charging power of the vehicle by no more than 20kW. After calculating the fluctuation parameters of all charging piles in the charging station, it is determined that the range of the fluctuation parameter is usually 1.0 3 to 1.18, so α is set to 0.01 to ensure that the calculation result of α×PD+1 is between 1 and 1.2, which is close to the range of the fluctuation parameter, so the influence is also close; for the pending charging pile A, the power difference PD is 0, and the fluctuation index is calculated to be 1.14×(0.01×0+1)=1.14; similarly, the fluctuation parameter of the pending charging pile B is calculated to be 1.03, and the power difference of the pending charging pile B is 10kW. Further calculation shows that the fluctuation index of the pending charging pile B is 1.08×(0.01×10+1)=1.133. The calculation result retains three decimal places. By sorting and numbering, P1 is the pending charging pile B, and P2 is the pending charging pile A.

[0095] The charging scheduling module is used to match the best idle charging pile for the vehicle or adopt different charging strategies based on the fluctuation index of idle charging piles and real-time vehicle data;

[0096] The charging scheduling module is configured with a charging scheduling strategy, which includes:

[0097] Get the charging mode. If the charging mode is slow charging, get the battery power and battery capacity, calculate BC-(BL×BC), and mark the calculation result as the amount to be charged, where BC is the battery capacity and BL is the battery power.

[0098] Get the rated power of the slow charging pile, named slow charging power, calculate the battery power divided by the slow charging power, and mark the calculation result as the estimated charging time;

[0099] In practical applications, it is assumed that the vehicle in this embodiment needs to be slowly charged, and the battery power is 40%, the battery capacity is 60kWh, and the amount to be charged is calculated to be 60kWh-(40%×60kWh)=36kWh; usually, in order to adapt to the different maximum charging power of different vehicles, the fast charging piles in the charging station also have different powers, and the slow charging is not affected by the maximum charging power. Therefore, the slow charging power of the slow charging piles in the charging station is generally the same; the slow charging power is obtained to be 6kW, and the estimated charging time is calculated to be 60kWh / 6kW=10h;

[0100] Obtain the current time, compare the current time with the first time threshold and the second time threshold, and if the current time is within the first time threshold and the second time threshold, output a normal charging signal; otherwise, output an energy-saving charging signal;

[0101] If a normal charging signal is output, the vehicle will be charged through a slow charging pile for half of the estimated charging time. Charging will be stopped after the time is reached. At the same time, the current grid power consumption is monitored in real time to see if it is off-peak power. If so, charging will continue until the vehicle is fully charged; if not, charging will be stopped until the off-peak power is reached and then continued;

[0102] If the energy-saving charging signal is output, the slow charging pile is controlled not to charge the vehicle, and the vehicle will be charged again when the power is low;

[0103] In actual applications, vehicles that choose slow charging usually do not move for a long time, and vehicles that choose slow charging are usually not used for long distances. A large amount of data statistics show that vehicles that choose slow charging after 18:00 usually move the vehicle the next morning. Therefore, the first time threshold is set to 0:00, and the second time threshold is set to 18:00. If a vehicle that chooses slow charging chooses slow charging between 0:00 and 18:00, it may need to use the vehicle at night, so it needs to be charged. In order to save charging costs, segmented charging is adopted. In the first case, the vehicle is charged for half of the estimated charging time, and the remaining half is charged when the electricity is off-peak. If the user needs to use the vehicle, the charged power is enough for the user to use. If the user does not need to use the vehicle, charging the vehicle when the electricity is off-peak can save charging costs. The time period of off-peak electricity is obtained according to the real-time update of the power grid system. In the second case, the user chooses slow charging after 18:00. At this time, the user basically does not move the vehicle, so the vehicle can be charged when the electricity is off-peak, which improves the utilization rate of off-peak electricity and reduces charging costs.

[0104] If the charging mode is fast charging, the pending charging pile of P1 is marked as the target charging pile, and the vehicle is assigned to the target charging pile;

[0105] In actual application, the driver chose fast charging, and P1 is the pending charging pile B, so the vehicle is assigned to the pending charging pile B; in this embodiment, although the power difference between the pending charging pile A and the vehicle is the smallest, and the charging resources can be maximized, the stability of the charging pile is far inferior to the pending charging pile B. The pending charging pile B can stably charge the vehicle while ensuring the utilization rate of charging resources, so that the charging time of the vehicle fluctuates less, avoiding the situation where the charging time of the vehicle increases due to current fluctuations of the charging pile.

[0106] The vehicle guidance module is used to guide the vehicle to the corresponding charging pile for charging through the guidance indicator light based on the matching charging pile;

[0107] The vehicle guidance module is configured with a vehicle guidance strategy, which includes:

[0108] If the charging mode is slow charging, the vehicle will be guided to any slow charging station through the guidance indicator light;

[0109] If the charging mode is fast charging, the vehicle will be guided to the target charging station through the guidance indicator light;

[0110] In actual application, after the driver scans the code and fills in the real-time vehicle data, the system analyzes the target charging pile and instructs the vehicle to go to the corresponding charging pile through the guide indicator light. The guide indicator light is set at each charging pile. After the driver completes the filling, the guide indicator light of the target charging pile lights up, and the vehicle can go to the lit guide indicator light for charging.

[0111] Example 2, please refer to Figure 4 As shown, the present application provides an optimization scheduling method for a new energy charging station, comprising the following steps:

[0112] Step S1, a vehicle data collection terminal is set at the entrance of the charging station. When a vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data; Step S1 includes the following sub-steps:

[0113] Step S101, the vehicle data collection terminal is a web program;

[0114] Step S102: When a vehicle enters a charging station, the driver scans a code to fill in the vehicle's real-time data, which includes battery power, vehicle brand and model, and charging mode. The charging mode includes fast charging and slow charging.

[0115] Step S2, obtaining the charging power of the vehicle battery based on the real-time data of the vehicle, and monitoring the status of the charging piles in the charging station in real time, and searching for idle charging piles; Step S2 includes the following sub-steps:

[0116] Step S201, obtaining the vehicle brand and model;

[0117] Step S202, searching the power database for the rated charging power and the rated battery capacity corresponding to the vehicle brand and model, and marking them as the charging power and the battery capacity respectively;

[0118] Step S203, the rated charging power and rated battery capacity of all new energy vehicles are recorded in the power database;

[0119] Step S204, monitoring the status of the charging piles in the charging station, and naming the idle charging piles in the charging station as idle charging piles;

[0120] Step S3, analyzing the fluctuation index of the idle charging pile; Step S3 includes the following sub-steps:

[0121] Step S301, obtaining the rated power of the idle charging pile;

[0122] Step S302, calculating the rated power minus the charging power, and marking the calculation result as the power difference;

[0123] Step S303: if the power difference of the idle charging piles is a negative number, then a power shortage signal is output; if the power difference of the idle charging piles is a non-negative number, then a power sufficient signal is output;

[0124] Step S304: if the output power is sufficient, the idle charging pile is marked as a pending charging pile;

[0125] Step S305, analyzing the fluctuation parameters of the pending electric piles based on the historical charging data of the pending electric piles, and sorting the pending electric piles in combination with the power difference;

[0126] Step S305 includes the following sub-steps:

[0127] Step S3051, for any pending charging pile, obtaining historical charging data of the pending charging pile, the historical charging data including historical estimated charging time and historical actual charging time;

[0128] Step S3052, calculate HAT / HET, and mark the calculation result as historical fluctuation, where HAT is the historical actual charging time and HET is the historical estimated charging time; count the number of different historical fluctuations, and name it as the fluctuation number;

[0129] Step S3053, creating a histogram with historical fluctuations as the X-axis and fluctuation quantity as the Y-axis, named as a fluctuation analysis histogram, and entering the historical fluctuations and the corresponding fluctuation quantity into the fluctuation analysis histogram;

[0130] Step S3054, obtaining the highest first analysis number of reference bars, naming them as the first reference bar, the second reference bar and the third reference bar in order from small to large heights, marking the range of historical fluctuations corresponding to the first reference bar to the second reference bar as the first range; marking the range of historical fluctuations corresponding to the first reference bar to the third reference bar as the second range; marking the range of historical fluctuations corresponding to the second reference bar to the third reference bar as the third range;

[0131] Step S3055, counting the union of the first range, the second range and the third range, marking it as a fluctuation union, and marking the historical fluctuations and the fluctuation quantity in the fluctuation union as fluctuations to be analyzed and the quantity to be analyzed respectively;

[0132] Step S3056: mark the number of fluctuations to be analyzed in the fluctuation set as symbol n, and the fluctuation to be analyzed and the number to be analyzed corresponding to the fluctuation to be analyzed are respectively marked with symbols W i and Q i Represents, where i is an integer and 1≤i≤n, and i is the sequence number of W and Q;

[0133] Step S3057, by formula Calculate the fluctuation parameter of the pending electric pile, where V is the fluctuation parameter;

[0134] Step S3058, calculate V×(α×PD+1), mark the calculation result as the fluctuation index, where PD is the power difference, α is the difference coefficient, mark the calculation result as the fluctuation index, sort and number the pending electric piles in the order of the fluctuation index from small to large, and use the symbol P m Indicates, where m is a non-zero natural number and m is the serial number of P;

[0135] Step S4, based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, matching the vehicle with the best idle charging pile or adopting different charging strategies; Step S4 includes the following sub-steps:

[0136] Step S401, obtaining the charging mode. If the charging mode is slow charging, obtaining the battery power and battery capacity, calculating BC-(BL×BC), and marking the calculation result as the amount to be charged, where BC is the battery capacity and BL is the battery power;

[0137] Step S402, obtaining the rated power of the slow charging pile, named as the slow charging power, calculating the battery power divided by the slow charging power, and marking the calculation result as the estimated charging time;

[0138] Step S403, obtaining the current time, comparing the current time with the first time threshold and the second time threshold, if the current time is within the first time threshold and the second time threshold, outputting a normal charging signal; otherwise, outputting an energy-saving charging signal;

[0139] Step S404: If a normal charging signal is output, the vehicle is charged through a slow charging pile, and the charging time is half of the estimated charging time. Charging is stopped after the time is reached, and the current grid power consumption is monitored in real time to see if it is off-peak power. If so, charging continues until the vehicle is fully charged; if not, charging is stopped until the off-peak power is reached and then charging is continued;

[0140] Step S405: If the energy-saving charging signal is output, the slow charging pile is controlled not to charge the vehicle, and the vehicle is charged again when the power is low;

[0141] Step S406: If the charging mode is fast charging, the pending charging pile of P1 is marked as the target charging pile, and the vehicle is assigned to the target charging pile;

[0142] Step S5, based on the matched charging pile, guide the vehicle to the corresponding charging pile for charging through the guide indicator light; Step S5 includes the following sub-steps:

[0143] Step S501, if the charging mode is slow charging, guide the vehicle to any slow charging pile through the guide indicator light;

[0144] Step S502: If the charging mode is fast charging, the vehicle is guided to the target charging station by the guidance indicator light.

[0145] Embodiment 3, the present application provides a structural schematic diagram of an electronic device, which may include: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in the optimization scheduling method of a new energy charging station are executed to achieve the following functions: a vehicle data acquisition terminal is set at the entrance of the charging station to collect real-time data of the vehicle; the charging power of the vehicle battery is obtained based on the real-time data of the vehicle; the fluctuation index of the idle charging pile is analyzed; based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, the best idle charging pile is matched for the vehicle or different charging strategies are adopted; the vehicle is guided to the corresponding charging pile for charging through the guide indicator light.

[0146] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0147] Embodiment 4, the present application also provides a computer-readable storage medium, the present application provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned optimization scheduling method of a new energy charging station are executed to achieve the following functions: a vehicle data acquisition terminal is set at the entrance of the charging station to collect real-time data of the vehicle; the charging power of the vehicle battery is obtained based on the real-time data of the vehicle; the fluctuation index of the idle charging pile is analyzed; based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, the best idle charging pile is matched for the vehicle or different charging strategies are adopted; the vehicle is guided to the corresponding charging pile for charging by the guide indicator light.

[0148] Through the description of the above implementation methods, the embodiments of the present invention can be provided as methods, systems or computer program products. Based on such an understanding, the above technical solutions can be essentially or partly contributed to the prior art in the form of software products, which can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and include several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0149] In the embodiments provided in the present application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of systems, modules and units can be electrical, mechanical or other forms.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing the scheduling of new energy charging stations, characterized in that: The steps include: A vehicle data collection terminal is set up at the entrance of the charging station. When a vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data; Obtain the charging power of the vehicle battery based on the real-time data of the vehicle, monitor the status of the charging piles in the charging station in real time, and find idle charging piles; Analyze the fluctuation index of idle charging piles; Based on the fluctuation index of idle charging piles and real-time vehicle data, the vehicle is matched with the best idle charging pile or different charging strategies are adopted; Based on the matching charging pile, the vehicle is guided to the corresponding charging pile for charging through the guidance indicator light; Analyzing the volatility index of idle charging piles includes the following sub-steps: Get the rated power of the idle charging pile; Calculate the rated power minus the charging power, and mark the result as the power difference; If the power difference of the idle charging piles is a negative number, an insufficient power signal is output; if the power difference of the idle charging piles is a non-negative number, a sufficient power signal is output; If the output power is sufficient, the idle charging pile is marked as a pending charging pile; Analyze the fluctuation parameters of the pending charging piles based on their historical charging data, and sort the pending charging piles based on the power difference; Analyzing the fluctuation parameters of the pending electric piles based on the historical charging data of the pending electric piles, and sorting the pending electric piles based on the power difference includes the following sub-steps: For any pending charging pile, obtain historical charging data of the pending charging pile, wherein the historical charging data includes historical estimated charging time and historical actual charging time; Calculate HAT / HET and mark the calculation result as historical fluctuation, where HAT is the historical actual charging time and HET is the historical estimated charging time; count the number of different historical fluctuations and name it as the fluctuation number; Create a histogram with historical fluctuations as the X-axis and fluctuation quantity as the Y-axis, named as fluctuation analysis histogram, and enter the historical fluctuations and the corresponding fluctuation quantity into the fluctuation analysis histogram; Obtain the highest first analysis number of benchmarks, and name them the first benchmark, the second benchmark, and the third benchmark in ascending order according to their heights; mark the range of historical fluctuations from the first benchmark to the second benchmark as the first range; mark the range of historical fluctuations from the first benchmark to the third benchmark as the second range; mark the range of historical fluctuations from the second benchmark to the third benchmark as the third range; Count the union of the first range, the second range and the third range, mark it as a fluctuation union, and mark the historical fluctuations and the number of fluctuations in the fluctuation union as fluctuations to be analyzed and the number to be analyzed respectively; The number of fluctuations to be analyzed in the fluctuation set is marked as symbol n, and the fluctuation to be analyzed and the number to be analyzed corresponding to the fluctuation to be analyzed are marked as symbol W respectively. i and Q i Represents, where i is an integer and 1≤i≤n, and i is the sequence number of W and Q; By formula Calculate the fluctuation parameter of the pending electric pile, where V is the fluctuation parameter; calculate , the calculation result is marked as the fluctuation index, where PD is the power difference, α is the difference coefficient, the calculation result is marked as the fluctuation index, and the pending electric piles are sorted and numbered in the order of the fluctuation index from small to large, and the symbol P is used to represent the fluctuation index. m Represents, where m is a non-zero natural number and m is the sequence number of P.

2. The optimization scheduling method of a new energy charging station according to claim 1 is characterized in that: A vehicle data collection terminal is set up at the entrance of the charging station. When a vehicle enters the charging station, the driver scans the code to fill in the vehicle's real-time data, which includes the following sub-steps: The vehicle data collection terminal is a web page program; When a vehicle enters a charging station, the driver scans a code to fill in the vehicle's real-time data, which includes battery power, vehicle brand and model, and charging mode, which includes fast charging and slow charging.

3. The optimization scheduling method of a new energy charging station according to claim 2 is characterized in that: Based on the real-time data of the vehicle, the charging power of the vehicle battery is obtained, and the status of the charging piles in the charging station is monitored in real time. Finding an idle charging pile includes the following sub-steps: Get the vehicle brand and model; Find the rated charging power and rated battery capacity corresponding to the vehicle brand and model in the power database, and mark them as charging power and battery capacity respectively; The power database records the rated charging power and rated battery capacity of all new energy vehicles; The status of the charging piles in the charging station is monitored, and the idle charging piles in the charging station are named idle charging piles.

4. The optimization scheduling method of a new energy charging station according to claim 3 is characterized in that: Based on the fluctuation index of idle charging piles and real-time vehicle data, matching the vehicle with the best idle charging pile or adopting different charging strategies includes the following sub-steps: Get the charging mode. If the charging mode is slow charging, get the battery power and battery capacity, calculate BC-(BL×BC), and mark the calculation result as the amount to be charged, where BC is the battery capacity and BL is the battery power. Get the rated power of the slow charging pile, named slow charging power, calculate the battery power divided by the slow charging power, and mark the calculation result as the estimated charging time; Obtain the current time, compare the current time with the first time threshold and the second time threshold, and if the current time is within the first time threshold and the second time threshold, output a normal charging signal; otherwise, output an energy-saving charging signal; If a normal charging signal is output, the vehicle will be charged through a slow charging pile for half of the estimated charging time. Charging will be stopped after the time is reached. At the same time, the current grid power consumption is monitored in real time to see if it is off-peak power. If so, charging will continue until the vehicle is fully charged; if not, charging will be stopped until the off-peak power is reached and then continued; If the energy-saving charging signal is output, the slow charging pile is controlled not to charge the vehicle, and the vehicle will be charged again when the power is low; If the charging mode is fast charging, the pending charging pile of P1 is marked as the target charging pile, and the vehicle is assigned to the target charging pile.

5. The optimization scheduling method of a new energy charging station according to claim 4 is characterized in that: Based on the matched charging pile, guiding the vehicle to the corresponding charging pile for charging through the guide indicator light includes the following sub-steps: If the charging mode is slow charging, the vehicle will be guided to any slow charging station through the guidance indicator light; If the charging mode is fast charging, the vehicle will be guided to the target charging station through the guidance indicator light.

6. An optimization scheduling system for a new energy charging station, used to implement an optimization scheduling method for a new energy charging station according to any one of claims 1 to 5, characterized in that: It includes a vehicle data acquisition module, a state monitoring module, a fluctuation analysis module, a charging scheduling module and a vehicle guidance module; the vehicle data acquisition module, the state monitoring module, the fluctuation analysis module and the vehicle guidance module are respectively connected to the charging scheduling module data; The vehicle data collection module is used to set a vehicle data collection terminal at the entrance of the charging station. When the vehicle enters the charging station, the driver scans the code to fill in the real-time data of the vehicle; The state monitoring module is used to obtain the charging power of the vehicle battery based on the real-time data of the vehicle, and at the same time monitor the state of the charging piles in the charging station in real time to find idle charging piles; The fluctuation analysis module is used to analyze the fluctuation index of the idle charging pile; The charging scheduling module is used to match the best idle charging pile for the vehicle or adopt different charging strategies based on the fluctuation index of the idle charging pile and the real-time data of the vehicle; The vehicle guidance module is used to guide the vehicle to the corresponding charging pile for charging through the guidance indicator light based on the matched charging pile.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1 to 5 are executed.

8. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are executed.

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