Charging power distribution method and electronic device

Abstract

The application relates to the charging technical field and discloses a charging power distribution method and electronic equipment. The charging power distribution method comprises the following steps: acquiring pile charging demand information of each charging pile in a target charging group, the target charging group comprising at least two charging piles; determining group actual distribution power of the target charging group, the group actual distribution power being the highest power distributed to the target charging group; determining pile upper limit power of each charging pile in the target charging group; and determining pile actual distribution power of each charging pile according to the group actual distribution power, the pile charging demand information and the pile upper limit power. According to the charging demand of a charging vehicle, the output power of each charging pile can be flexibly adjusted, the charging demand of each charging vehicle can be maximally satisfied, meanwhile, the recovery and release of the redundant power among the charging piles can be realized, and the power utilization efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of charging technology, specifically to a charging power distribution method and electronic device. Background Technology

[0002] Electric vehicle charging stations are similar to gas stations, both being facilities that replenish vehicle energy. Charging stations typically have multiple charging piles, each capable of charging an electric vehicle. Charging stations usually have a power limit; when multiple charging piles are charging an electric vehicle, the total power output from all charging piles cannot exceed this limit. To avoid this issue of multiple vehicles charging simultaneously exceeding the maximum power limit, traditional technology typically limits the maximum output power of each charging pile. However, traditional technology often suffers from unreasonable power distribution, failing to meet the charging needs of every vehicle and reducing the power utilization efficiency of the charging station. Summary of the Invention

[0003] One objective of this application is to provide a charging power distribution method and electronic device that can solve the technical problem of unreasonable charging power distribution in conventional technologies.

[0004] In a first aspect, embodiments of this application provide a charging power allocation method, comprising:

[0005] Obtain charging demand information for each charging pile within the target charging group, wherein the target charging group includes at least two charging piles;

[0006] Determine the actual power allocated to the target charging group, where the actual power allocated to the target charging group is the highest power allocated to the target charging group;

[0007] Determine the maximum power output of each charging pile within the target charging group;

[0008] The actual power allocated to each charging pile is determined based on the charging demand information of the pile, the actual power allocated to the group, and the upper limit power of the pile.

[0009] Optionally, determining the actual power allocation for each charging pile based on the charging demand information, the actual power allocation for the group, and the upper limit power of the pile includes:

[0010] Obtain the pile decision variables and pile constraints corresponding to each charging pile, wherein the pile decision variables include the pile allocation power variables used to solve the actual allocated power of the pile;

[0011] The pile constraint conditions are generated based on the pile constraint conditions and the first type of parameters, and the first type of parameters includes the pile charging demand information, the pile upper limit power, the pile allocation power variable or the group actual allocation power.

[0012] Generate the pile objective function based on the pile decision variables;

[0013] The actual power allocation for each charging pile is determined based on the pile constraint conditions after input parameters and the pile objective function.

[0014] Optionally, the pile decision variables further include pile power adjustment variables, the pile constraints include pile charging demand constraints, the pile charging demand information includes the required charging time and the required charging power, and the pile constraints generated based on the pile constraints and the first type of parameters include:

[0015] Obtain the first type of parameters corresponding to the charging demand constraints of the pile: the charging time required for the pile, the charging power required for the pile, and the pile power adjustment variable;

[0016] Based on the charging time required for the pile, the charging power required for the pile, and the pile power adjustment variable, the pile charging demand constraint is generated as input parameters. The pile charging demand constraint is used to ensure that the product of the pile power allocation variable and the charging time required for the pile is greater than or equal to the difference between the charging power required for the pile and the pile power adjustment variable.

[0017] Optionally, the pile constraint conditions include pile charging power constraint conditions, and the first type of parameters further includes a preset lower limit power and a preset upper limit power for the pile. The pile constraint conditions generated based on the pile constraint conditions and the first type of parameters include:

[0018] Obtain the first type of parameters corresponding to the charging power constraint of the pile: the pile power allocation variable, the pile upper limit power, the pile preset lower limit power and the pile preset upper limit power;

[0019] Based on the pile power allocation variable, the pile upper limit power, the pile preset lower limit power, and the pile preset upper limit power, the pile charging power constraint condition is generated after input parameters are generated. The pile charging power constraint condition is used to constrain the pile power allocation variable to be greater than or equal to the pile preset lower limit power, and less than or equal to the minimum value of the pile upper limit power and the pile preset upper limit power.

[0020] Optionally, the pile constraint conditions include total pile power distribution constraint conditions, and the pile constraint conditions generated based on the pile constraint conditions and the first type of parameters after input parameters are generated include:

[0021] Obtain the first type of parameters corresponding to the total power distribution constraint of the piles: the power distribution variable of the piles and the actual power distribution of the group;

[0022] Based on the pile allocation power variables and the actual group allocation power, the total pile allocation power constraint condition is generated after input parameters. The total pile allocation power constraint condition is used to constrain the sum of the pile allocation power variables corresponding to all charging piles to be less than or equal to the actual group allocation power.

[0023] Optionally, the pile objective function includes a first objective function and a second objective function, and generating the pile objective function based on the pile decision variables includes:

[0024] The pile allocation power variable corresponding to each charging pile is summed to obtain the first objective function, which is configured to take the maximum value.

[0025] The average value of the pile distribution power is obtained by averaging the pile distribution power variables.

[0026] The absolute value of the pile allocation power variable is obtained by subtracting the average pile allocation power from the pile allocation power variable corresponding to each charging pile and taking the absolute value.

[0027] The power allocation deviation of each charging pile is accumulated to obtain the second objective function, which is configured to take the minimum value.

[0028] Optionally, the pile decision variables further include pile power adjustment variables, and the pile objective function further includes a third objective function and a fourth objective function. Generating the pile objective function based on the pile decision variables includes:

[0029] The third objective function is obtained by summing up the pile power adjustment variables corresponding to each charging pile, and the third objective function is configured to take the minimum value.

[0030] The average value of the pile power adjustment variable is obtained by averaging the pile power adjustment variables.

[0031] Subtract the average value of the pile power adjustment from the pile power adjustment variable corresponding to each charging pile, and then take the absolute value to obtain the pile power adjustment deviation corresponding to each charging pile.

[0032] The fourth objective function is obtained by summing up the pile power adjustment deviations corresponding to each charging pile, and the fourth objective function is configured to take the minimum value.

[0033] Optionally, it also includes:

[0034] Based on the first objective function and the first weight coefficient, the second objective function and the second weight coefficient, the third objective function and the third weight coefficient, and the fourth objective function and the fourth weight coefficient, a weighted sum of objective functions is calculated, and the weighted sum of objective functions is used as the final piling objective function.

[0035] Optionally, determining the actual power allocation for the target charging group includes:

[0036] Obtain the maximum power output of the charging station;

[0037] The group charging demand information of each charging group in the charging station is determined based on the pile charging demand information of each charging pile in each charging group.

[0038] Determine the maximum power limit for each charging group within the charging station;

[0039] The actual power allocation for each charging group is determined based on the station's maximum power capacity, the group charging demand information, and the group's maximum power capacity.

[0040] Optionally, determining the maximum power output of each charging pile within the target charging group includes:

[0041] Obtain the design power of each charging pile and the upper limit of charging power for the vehicle corresponding to each charging pile;

[0042] Determine whether the charging time of the vehicle being charged is less than a preset time;

[0043] If it is less than the preset time, the minimum value between the upper limit charging power of the charging vehicle and the pile design power of the charging pile corresponding to the charging vehicle is determined to be the upper limit charging power of the charging pile.

[0044] If the power is greater than or equal to the preset duration, the reported power of the charging vehicle is obtained. Based on the reported power of the charging vehicle and the preset compensation threshold, the required power of the charging vehicle is determined, and the minimum value of the required power of the charging vehicle, the upper limit power of charging, and the design power of the charging pile corresponding to the charging vehicle is determined as the upper limit power of the charging pile.

[0045] In a second aspect, embodiments of this application provide an electronic device including at least one processor; and,

[0046] A memory communicatively connected to the at least one processor; wherein,

[0047] The memory stores commands that can be executed by the at least one processor, which enable the at least one processor to perform the charging power distribution method as described above.

[0048] In a third aspect, embodiments of this application provide a non-volatile computing storage medium storing computer-executable commands for causing an electronic device to perform the charging power distribution method described above.

[0049] The charging power allocation method provided in this application includes: acquiring the charging demand information of each charging pile in a target charging group, wherein the target charging group includes at least two charging piles; determining the actual group-allocated power of the target charging group, wherein the actual group-allocated power is the highest power allocated to the target charging group; determining the upper limit power of each charging pile in the target charging group; and determining the actual pile-allocated power of each charging pile based on the actual group-allocated power, the charging demand information, and the upper limit power. This embodiment can flexibly adjust the output power of each charging pile according to the charging demand of the charging vehicle, thereby maximizing the satisfaction of the charging demand of each charging vehicle and also realizing the recovery and release of excess power between charging piles, thus improving power utilization efficiency. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a schematic diagram of a charging power distribution system provided in an embodiment of this application;

[0052] Figure 2 This is a schematic flowchart of a charging power allocation method provided in an embodiment of this application;

[0053] Figure 3 yes Figure 2 The flowchart of S21 is shown below;

[0054] Figure 4 yes Figure 3 The flowchart of S214 is shown below;

[0055] Figure 5 yes Figure 2 The flowchart of S24 is shown below;

[0056] Figure 6 This is a schematic diagram of the structure of a charging power distribution device provided in an embodiment of this application;

[0057] Figure 7 yes Figure 6 The diagram shows the structure of the third determining module 64.

[0058] Figure 8 yes Figure 6 The diagram shows the structure of the first determining module 62.

[0059] Figure 9 yes Figure 6 The diagram shows the structure of the second determining module 63.

[0060] Figure 10 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0062] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. Moreover, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0063] This application provides a charging power distribution system. Please refer to [link / reference]. Figure 1 The charging power distribution system includes a charging station 100 and a charging management device 200.

[0064] Charging station 100 is a facility that provides charging services for electric vehicles within cities, highways, or industrial areas. Charging station 100 includes at least one charging group, such as... Figure 1 As shown, the charging station 100 includes a first charging group 10 and a second charging group 20. It is understood that the charging station 100 may also include a greater number of charging groups, such as three or more.

[0065] The charging group can be a single-layer charging group or a multi-layer charging group. For example, if the first charging group 10 is a single-layer charging group, there are no subdivided charging groups within the first charging group 10. If the first charging group 10 is a multi-layer charging group, there are subdivided charging groups within the first charging group 10. For example, the first charging group 10 includes a third charging group and a fourth charging group.

[0066] It is worth noting that, for ease of description, unless otherwise specified, all charging groups in the charging stations mentioned below are single-layer charging groups.

[0067] Each charging group includes at least two charging stations, each capable of charging vehicles. For example, such as Figure 1 As shown, the first charging group 10 includes a first charging pile 11, a second charging pile 12 and a third charging pile 13. The first charging pile 11 is charging the first charging vehicle A, the second charging pile 12 is charging the second charging vehicle B, and the third charging pile 13 is charging the third charging vehicle C.

[0068] During the charging process, the charging station can report its required power to the charging station in real time, so that the charging station can then issue the power required to meet the charging needs of the vehicle.

[0069] The charging stations in charging station 100 can be divided into charging groups according to actual needs. For example, charging piles using the same power supply point can be grouped into one charging group. Figure 1 As shown, the first charging pile 11, the second charging pile 12 and the third charging pile 13 use the first power supply point, and the fourth charging pile 21, the fifth charging pile 22 and the sixth charging pile 23 use the second power supply point. The first power supply point and the second power supply point are different power supply points.

[0070] The charging management device 200 is communicatively connected to each charging pile in each charging group within the charging station 100. It can interact with each charging pile, sending and receiving various information from them. The charging management device 200 can obtain various information about the vehicles currently charging through the charging piles, such as... Figure 1 As shown, after obtaining the information of the first charging vehicle A, the charging pile 11 can send the information of the first charging vehicle A to the charging management device 200.

[0071] The charging management device 200 can integrate various information about charging vehicles, power grid load information, and charging pile information, and manage the power of each charging group and the power of each charging pile within each charging group based on this information.

[0072] In some embodiments, the charging management device 200 may consist of one or more workstations or servers, enabling monitoring and data collection and querying of charging piles, as well as data processing and analysis of the entire charging station. The charging management device 200 serves as the algorithm execution core of the charging power allocation system, used to execute the charging power allocation method described below.

[0073] This application provides a charging power allocation method. Please refer to [link / reference]. Figure 2 The charging power allocation methods include:

[0074] S21. Obtain the charging demand information of each charging pile in the target charging group;

[0075] In this step, the target charging group can be any charging group within the charging station. The charging pile demand information refers to the charging demand information of the vehicles using the charging pile for charging. Each charging pile can send the acquired charging demand information to the charging management equipment for algorithmic calculation. The charging demand information can include any information that indicates that a vehicle has a charging demand.

[0076] In some embodiments, the charging demand information includes the charging time required for the charging vehicle to be charged at the charging pile and the charging power required for the charging pile. The charging time required refers to the charging time set by the user for the charging vehicle being charged through the charging pile, and the charging power required refers to the charging power set by the user for the charging vehicle being charged through the charging pile.

[0077] S22. Determine the actual power allocation of the target charging group;

[0078] In this step, the actual group power allocation is the power actually allocated to the target charging group by the charging management device when performing power allocation within the charging station. The charging management device can simultaneously determine the actual group power allocation for each charging group in the charging station, ensuring that the sum of the actual group power allocation for all charging groups does not exceed the charging station's upper limit power. The upper limit power is the maximum total power that the charging station can allocate to all charging groups within that charging station. For example, as mentioned earlier, based on a charging station upper limit power of 100 kW, the charging management device determines that the actual group power allocation for the first charging group is 55 kW and the actual group power allocation for the second charging group is 45 kW.

[0079] Understandably, for charging stations with single-layer and multi-layer charging groups, the charging management equipment can first determine the actual power allocation of multiple parallel charging groups within the charging station, and then determine the actual power allocation of each charging group in the multi-layer charging group. As mentioned earlier, assuming the first charging group includes the third and fourth charging groups, after the charging management equipment determines that the actual power allocation of the first charging group is 55 kW, it can further determine the actual power allocation of the third and fourth charging groups, for example, determining that the actual power allocation of the third charging group is 30 kW and the actual power allocation of the fourth charging group is 25 kW, ensuring that the sum of the actual power allocation of the third and fourth charging groups does not exceed the actual power allocation of the first charging group.

[0080] S23. Determine the maximum power of each charging pile within the target charging group;

[0081] In this step, the upper limit power of the charging pile is the maximum power of the charging pile.

[0082] In some embodiments, the charging management device acquires the design power of each charging pile and the upper limit power of the charging vehicle corresponding to each charging pile, determines whether the charging time of the charging vehicle is less than a preset time, if it is less than the preset time, determines the lower limit power of the charging vehicle and the design power of the charging pile corresponding to the charging vehicle as the upper limit power of the charging pile, if it is greater than or equal to the preset time, acquires the reported power of the charging vehicle, determines the required power of the charging vehicle based on the reported power of the charging vehicle and a preset compensation threshold, and determines the lower limit power of the charging pile as the lower limit power of the charging pile, which is the minimum of the required power of the charging vehicle, the upper limit power of the charging vehicle and the design power of the charging pile corresponding to the charging vehicle.

[0083] In this embodiment, the charging pile design power refers to the maximum output power that the charging pile is designed to output, the charging upper limit power refers to the maximum charging power that the charging vehicle is designed to charge, the reported power refers to the power reported by the charging vehicle during the charging process, and the preset compensation threshold is the compensation power designed to compensate for the charging loss that exists in the charging pile during the charging process of the charging vehicle.

[0084] During the charging process, the charging power demand of a vehicle varies at different times. Generally, the charging power demand is relatively high when the vehicle first starts charging. After a certain charging time, the battery capacity of the vehicle approaches full charge, at which point the vehicle will automatically reduce the charging power and enter the trickle charging stage, resulting in a lower reported power. Therefore, by combining the charging time and the reported power to determine the upper limit power of the charging station, power waste can be avoided while meeting the charging needs of the vehicle.

[0085] For example, the first charging pile has a designed power of 20 kW. The maximum charging power of the first vehicle using the first charging pile is 15 kW. Typically, the power reported by the vehicle before it has been charging for 30 minutes does not need to be considered. Therefore, the charging management equipment can determine the minimum value of 15 kW (the minimum of the pile's designed power of 20 kW and the maximum charging power of 15 kW) as the maximum charging power. However, after 30 minutes of charging, the power reported by the vehicle may be lower, for example, 10 kW. If charging is still configured... If a charging pile uses 15 kW to charge a vehicle, it cannot match the actual charging needs of the vehicle and may cause power waste. Therefore, after the vehicle has been charging for 30 minutes, the charging management equipment can determine the minimum value among the pile's design power, the charging upper limit power, the reported power, and the preset compensation threshold as the pile's upper limit power. For example, the charging management equipment can determine the minimum value of 10.1 kW (i.e., 10.1 kW) among the pile's design power of 20 kW, the charging upper limit power of 15 kW, the reported power of 10 kW, and the preset compensation threshold of 0.1 kW as the pile's upper limit power.

[0086] When the upper limit power of any charging pile in any charging group changes, as mentioned above, assuming the upper limit power of the first charging pile changes from 15 kW to 10.1 kW, in order to realize the recovery and release of excess power between charging piles, the charging management device returns to execute S21, that is, the charging management device redetermines the actual group allocation power of each charging group, and then adjusts the pile allocation power of each charging pile in each charging group based on the redetermined actual group allocation power of each charging group.

[0087] S24. Determine the actual power allocated to each charging pile based on the actual power allocation of the group, the charging demand information of the charging pile, and the upper limit power of the charging pile.

[0088] In this step, the actual power allocated to a charging pile is the power actually allocated to the charging pile when the charging management device allocates power within the charging group. Since the actual power allocated to a charging pile is based on the pile's upper limit power and is allocated according to the actual needs of each charging pile, generally speaking, the actual power allocated to each charging pile is less than or equal to the pile's upper limit power. For example, if the upper limit power of the first charging pile is 15 kW, the actual power allocated to the first charging pile is 14.5 kW.

[0089] The charging management equipment can use any suitable on-demand allocation algorithm to determine the actual power allocation of each charging pile based on the actual power allocation of the group, the charging demand information of the charging pile, and the upper limit power of the charging pile, so as to realize the power allocation of each charging pile on demand.

[0090] Therefore, this embodiment can flexibly adjust the output power of each charging pile according to the charging needs of the charging vehicle, so as to meet the charging needs of each charging vehicle to the greatest extent, while also realizing the recovery and release of excess power between charging piles and improving power utilization efficiency.

[0091] In some embodiments, please refer to Figure 3 S21 includes:

[0092] S211. Obtain the maximum power of the charging station;

[0093] It should be noted that the maximum power output of a charging station is typically determined by factors such as the station's design, equipment configuration, and power grid capacity, and is generally fixed. However, it may be adjusted as the charging station is upgraded or renovated. In some embodiments, the maximum power output may also vary based on the grid capacity of the area where the charging station is located.

[0094] S212. Determine the group charging demand information of each charging group in the charging station based on the pile charging demand information of each charging pile in each charging group.

[0095] In this step, the charging pile demand information includes the amount of electricity required for charging and the duration required for charging.

[0096] For the first charging group, for example, the charging power required for the first charging pile and the charging time required are e1 and t1 respectively, the charging power required for the second charging pile and the charging time required are e2 and t2 respectively, and the charging power required for the third charging pile and the charging time required are e3 and t3 respectively.

[0097] For the second charging group, for example, the charging power required for the fourth charging pile and the charging time required are e4 and t4 respectively, the charging power required for the fifth charging pile and the charging time required are e5 and t5 respectively, and the charging power required for the sixth charging pile and the charging time required are e6 and t6 respectively.

[0098] The group charging demand information includes the required power and duration of group charging. The required power is the total power needed for the target charging group, and the required duration is the total duration of the target charging group. In some embodiments, the charging management device adds up the power required for each charging pile within each charging group to obtain the required power for the group charging, and adds up the duration required for each charging pile within each charging group to obtain the required duration of the group charging.

[0099] As mentioned above, for the first charging group, the amount of electricity required for group charging is E1, which is e1+e2+e3, and the time required for group charging is T1, which is t1+t2+t3. For the second charging group, the amount of electricity required for group charging is E2, which is e4+e5+e6, and the time required for group charging is T2, which is t4+t5+t6.

[0100] S213. Determine the maximum power limit of each charging group within the charging station;

[0101] In this step, the maximum power of the group is the highest power of the charging group.

[0102] In some embodiments, the charging management device obtains the preset maximum power of each charging group and the designed power of each charging pile within each charging group, adds the designed power of all charging piles within each charging group to obtain the sum of the designed power of each pile, and then takes the minimum value of the preset maximum power and the sum of the designed power of each pile as the upper limit power of the group. The preset maximum power can be customized according to actual needs.

[0103] For example, the preset maximum power of the first charging group is 58 kilowatts, and the designed power of each of the three charging piles in the first charging group is 20 kilowatts. That is, the sum of the designed power of the three charging piles in the first charging group is 60 kilowatts. Therefore, the charging management device determines the minimum value of the preset maximum power of 58 kilowatts and the sum of the designed power of the piles of 60 kilowatts, 58 kilowatts, as the upper limit power of the first charging group.

[0104] For another example, the preset maximum power of the second charging group is 48 kilowatts, and the designed power of each of the three charging piles in the second charging group is 15 kilowatts. Since the sum of the designed power of the three charging piles in the second charging group is 45 kilowatts, the charging management equipment determines that the minimum value of the preset maximum power of 48 kilowatts and the sum of the designed power of the piles of 45 kilowatts, 45 kilowatts, is 45 kilowatts, as the upper limit power of the second charging group.

[0105] S214. Determine the actual power allocation for each charging group based on the station's maximum power, group charging demand information, and the group's maximum power.

[0106] In this step, the charging management device can use any suitable on-demand allocation algorithm to determine the actual power allocation for each charging group based on the station's maximum power, group charging demand information, and group maximum power, thereby achieving on-demand power allocation for each charging group.

[0107] Therefore, this embodiment can flexibly adjust the output power of each charging group according to the charging needs of the charging group, so as to meet the charging needs of each charging group to the greatest extent, while also realizing the recovery and release of excess power between charging groups and improving power utilization efficiency.

[0108] In some embodiments, please refer to Figure 4 S214 includes:

[0109] S2141. Obtain the group decision variables and group constraints corresponding to each charging group. The group decision variables include the group allocation power variables used to solve the actual allocation power of the group.

[0110] In this step, the group decision variables are pre-assumed variables, and each charging group can be configured with a corresponding group decision variable. For example, the first charging group is configured with the group allocation power variable Var1[EASE], and the second charging group is configured with the group allocation power variable Var2[EASE].

[0111] Group constraints are conditions used to constrain group decision variables. Those skilled in the art can set the number and type of group constraints according to actual needs. Different group constraints have different constraint types.

[0112] S2142. Based on the group constraint conditions and the group constraint conditions generated with the second type of parameters after the input parameters are generated;

[0113] In some embodiments, the second type of parameters includes the station's upper limit power, group charging demand information, group upper limit power, group allocated power variable, group preset lower limit power, or group preset upper limit power, wherein the group preset lower limit power is the minimum power preset for the charging group according to actual demand, and the group preset upper limit power is the maximum power preset for the charging group according to actual demand.

[0114] In some embodiments, the group constraint conditions include group charging power constraint conditions. The charging management device can obtain a second type of parameter corresponding to the group charging power constraint conditions: group allocation power variable, group upper limit power, group preset lower limit power, and group preset upper limit power. The device can generate the group charging power constraint conditions after input parameters based on the group allocation power variable, group upper limit power, group preset lower limit power, and group preset upper limit power. For example, the charging management device can substitute the group allocation power variable, group upper limit power, group preset lower limit power, and group preset upper limit power into the group charging power constraint conditions to obtain the group charging power constraint conditions after input parameters.

[0115] In some embodiments, the group charging power constraint is expressed by the following formula:

[0116] model.Add(min_C≤Var[EASE]≤min(sn_LIMIT,user_LIMIT))

[0117] Where min_C is the group's preset lower limit power, Var[EASE] is the group's allocated power variable, and min(sn_LIMIT,user_LIMIT) means taking the minimum value between sn_LIMIT and user_LIMIT, where sn_LIMIT is the group's upper limit power and user_LIMIT is the group's preset upper limit power.

[0118] As can be seen from this formula, the group charging power constraint condition can constrain the group allocation power variable to be greater than or equal to the group preset lower limit power, and less than or equal to the minimum value between the group upper limit power and the group preset upper limit power.

[0119] For example, for the first charging group, the group charging power constraint after input parameters is expressed by the following formula:

[0120] model.Add(min_C1≤Var1[EASE]≤min(sn_LIMIT1,user_LIMIT1))

[0121] Wherein, min_C1 is the preset lower limit power of the first charging group, Var1[EASE] is the group allocated power variable corresponding to the first charging group, sn_LIMIT1 is the upper limit power of the first charging group, and user_LIMIT1 is the preset upper limit power of the first charging group.

[0122] For the second charging group, the group charging power constraint condition after input parameters is expressed by the following formula:

[0123] model.Add(min_C2≤Var2[EASE]≤min(sn_LIMIT2,user_LIMIT2))

[0124] Wherein, min_C2 is the preset lower limit power of the second charging group, Var2[EASE] is the group allocated power variable corresponding to the second charging group, sn_LIMIT2 is the upper limit power of the second charging group, and user_LIMIT2 is the preset upper limit power of the second charging group.

[0125] Therefore, this embodiment constrains the actual power allocation of each charging group within a certain power range by using the group charging power constraint condition. This ensures that the actual power allocation of each charging group will not exceed the range, making the final actual power allocation more in line with actual needs.

[0126] In some embodiments, the group constraint conditions include the total group power allocation constraint conditions. The charging management device can obtain the second type of parameters corresponding to the total group power allocation constraint conditions: the group power allocation variable and the station upper limit power. Based on the group power allocation variable and the station upper limit power, the charging management device can generate the group power allocation constraint conditions after input parameters. For example, the charging management device can substitute the group power allocation variable and the station upper limit power into the group power allocation constraint conditions to obtain the group power allocation constraint conditions after input parameters.

[0127] In some embodiments, the group total power allocation constraint is expressed by the following formula:

[0128] model.Add(sum(Var[EASE]for EASE in Var)≤up_LIMIT)

[0129] Where sum(Var[EASE]for EASE in Var) means summing the group allocation power variables corresponding to all charging groups in the charging station, and up_LIMIT is the station's upper limit power.

[0130] As can be seen from this formula, the group total power allocation constraint condition can ensure that the sum of the group power allocation variables corresponding to all charging groups is less than or equal to the station's upper limit power.

[0131] For example, the group total power distribution constraint after parameter input is expressed by the following formula:

[0132] model.Add(Var1[EASE]+Var2[EASE]≤up_LIMIT)

[0133] Therefore, this embodiment ensures that the sum of the actual power allocated to all charging groups is less than or equal to the upper limit power of the charging station by constraining the total power allocated to the group.

[0134] In some embodiments, the group decision variables also include group power adjustment variables, which are decision variables used to solve the charging power adjustment value of each charging group. By introducing group power adjustment variables, it can be ensured that the global optimal solution of the actual power allocation of the group is solved, and there will be no case where there is only a local optimal solution. A local optimal solution means that the actual power allocation of some charging groups has a solution, while the actual power allocation of some charging groups has no solution.

[0135] It is understandable that when a user's charging demand is set unreasonably within a limited time and exceeds the charging range, without the introduction of a group power adjustment variable, the solution may fail to meet the power demand of all charging groups. In this case, it may lead to the problem that the actual power allocation of some charging groups is unsolvable.

[0136] In some embodiments, the group constraint conditions include group charging demand constraints. The charging management device can obtain a second type of parameter corresponding to the group charging demand constraints: group allocation power variable and group power adjustment variable, and generate the group charging demand constraints after input parameters based on the group allocation power variable and group power adjustment variable. For example, the charging management device can substitute the group allocation power variable, group charging demand constraints and group power adjustment variable into the group charging demand constraints to obtain the group charging demand constraints after input parameters.

[0137] In some embodiments, the group charging demand constraint is expressed by the following formula:

[0138] model.Add(Var[EASE]*T≥(E-E_alp[EASE])*60)

[0139] Where T is the time required for group charging, E is the amount of electricity required for group charging, and E_alp[EASE] is the group electricity adjustment variable.

[0140] As can be seen from this formula, the group charging demand constraint is used to ensure that the product of the group power allocation variable and the group charging time is greater than or equal to the difference between the group charging power and the group power adjustment variable.

[0141] In some embodiments, the unit of the time T required for group charging is usually minutes, while the units of the amount of electricity required for group charging E and the group electricity adjustment variable E_alp[EASE] are both kilowatt-hours. Therefore, by multiplying the difference between the amount of electricity required for group charging E and the group electricity adjustment variable E_alp[EASE] by 60, the unit of the time T required for group charging can be converted from minutes to hours.

[0142] For example, for the first charging group, the group charging demand constraint after input parameters can be expressed by the following formula:

[0143] model.Add(Var1[EASE]*T1≥(E1-E_alp1[EASE])*60)

[0144] Where Var1[EASE] is the group power allocation variable corresponding to the first charging group, T1 is the group charging time required for the first charging group, E1 is the group charging power required for the first charging group, and E_alp1[EASE] is the group power adjustment variable corresponding to the first charging group.

[0145] For the second charging group, the group charging demand constraint after input parameters is expressed by the following formula:

[0146] model.Add(Var2[EASE]*T2≥(E2-E_alp2[EASE])*60)

[0147] Where Var2[EASE] is the group power allocation variable corresponding to the second charging group, T2 is the group charging time required for the second charging group, E2 is the group charging power required for the second charging group, and E_alp2[EASE] is the group power adjustment variable corresponding to the second charging group.

[0148] Therefore, this embodiment ensures that each charging group meets its charging needs by constraining the charging capacity of each charging group to be greater than or equal to the adjusted value through group charging demand constraints.

[0149] S2143. Generate the group objective function based on the group decision variables;

[0150] In this step, the group objective function is the desired objective expressed in terms of group decision variables, and it is also a function of the group decision variables. Those skilled in the art can set the number of group objective functions according to actual needs, where different objective functions are used to achieve different optimization objectives.

[0151] In some embodiments, the group objective function includes a fifth objective function, which is obtained by the charging management device accumulating the group allocation power variable corresponding to each charging group. The fifth objective function is configured to take the maximum value.

[0152] In some embodiments, the fifth objective function s5 is expressed as follows:

[0153] s5=sum(Var[EASE]for EASE in Var)

[0154] Where sum(Var[EASE]for EASE in Var) represents the sum of the group allocation power variables corresponding to all charging groups within the charging station.

[0155] For example, the fifth objective function can be expressed as follows:

[0156] s5 = Var1[EASE] + Var2[EASE]

[0157] Therefore, this embodiment optimizes the total power allocation of the group by using the fifth objective function to maximize the utilization of the charging station's power, thereby improving the charging efficiency of the charging station.

[0158] In some embodiments, the group objective function includes a sixth objective function. The charging management device averages the group allocation power variable to obtain the average group allocation power. The absolute value of the group allocation power variable corresponding to each charging group is obtained by subtracting the average group allocation power from the group allocation power variable corresponding to each charging group. The group allocation power deviation corresponding to each charging group is accumulated to obtain the sixth objective function, which is configured to take the minimum value.

[0159] In some embodiments, the sixth objective function s6 is expressed as follows:

[0160] s6=sum(diff1[EASE]for EASE in diff1)

[0161] model.Add=(var_S==sum(Var[EASE]for EASE in Var))

[0162] model.AddDivisionEquality=(mean1,var_S,int(len(Var)))

[0163] model.Add(diff11[EASE]==Var[EASE]-mean1)

[0164] model.AddAbsEquality(diff1[EASE],diff11[EASE])

[0165] Where Var_S is the sum of the group allocation power variables corresponding to all charging groups in the charging station, mean1 is the mean of group allocation power, diff11[EASE] is the difference between the group allocation power and the mean of group allocation power for each charging group, diff1[EASE] is the deviation of group allocation power for each charging group, and sum(diff1[EASE]forEASE in diff1) means summing the deviations of group allocation power corresponding to all charging groups in the charging station.

[0166] For example, the sixth objective function can be expressed as follows:

[0167] s6=|Var1[EASE]-Var12[EASE]|+|Var2[EASE]-Var12[EASE]|

[0168]

[0169] Therefore, this embodiment optimizes the group power distribution deviation by minimizing the deviation through the sixth objective function, which can maximize the satisfaction of the power demand of each charging group, thereby improving the rationality of power allocation at charging stations.

[0170] In some embodiments, the group objective function includes a seventh objective function, which is obtained by the charging management device accumulating the group power adjustment variable corresponding to each charging group. The seventh objective function is configured to take the minimum value.

[0171] In some embodiments, the seventh objective function s7 is represented by the following formula:

[0172] s7=sum(E_alp[EASE]for EASE in E_alp)

[0173] Here, sum(E_alp[EASE]for EASE in E_alp) means summing up the group power adjustment variables corresponding to all charging groups within the charging station.

[0174] For example, the seventh objective function can be expressed as follows:

[0175] s7=E_alp1[EASE]+E_alp2[EASE]

[0176] Therefore, this embodiment optimizes the total adjustment of the group by minimizing the total power of the group through the seventh objective function, which can minimize the power adjustment of each charging group in the charging station while ensuring that the actual power allocation of the group has a solution.

[0177] In some embodiments, the group objective function includes an eighth objective function. The charging management device averages the group power adjustment variable to obtain the group power adjustment mean. The absolute value of the group power adjustment variable corresponding to each charging group is obtained by subtracting the group power adjustment mean from the group power adjustment variable corresponding to each charging group. The group power adjustment deviation corresponding to each charging group is accumulated to obtain the eighth objective function, which is configured to take the minimum value.

[0178] In some embodiments, the eighth objective function s8 is expressed as follows:

[0179] s8=sum(diff2[EASE]for EASE in diff2)

[0180] model.Add=(ealp_S==sum(E_alp[EASE]for EASE in E_alp))

[0181] model.AddDivisionEquality=(mean2,ealp_S,int(len(E_alp)))

[0182] model.Add(diff22[EASE]==E_alp[EASE]-mean2)

[0183] model.AddAbsEquality(diff2[EASE],diff22[EASE])

[0184] Where, ealp_S is the sum of the group power adjustment variables corresponding to all charging groups, mean2 is the mean of group power adjustment, diff22[EASE] is the difference between the group power adjustment variable and the mean of group power adjustment for each charging group, diff2[EASE] is the group power adjustment deviation for each charging group, and sum(diff2[EASE]for EASE indiff2) means summing the group power adjustment deviations corresponding to all charging groups in the charging station.

[0185] For example, the eighth objective function can be expressed as follows:

[0186] s8=|E_alp1[EASE]-E_alp12[EASE]|+|E_alp2[EASE]-E_alp12[EASE]|

[0187]

[0188] Therefore, this embodiment optimizes the group power adjustment deviation by minimizing the deviation through the eighth objective function, which can maximize the satisfaction of the charging power demand of each charging group while ensuring that the actual power allocation of the group has a solution.

[0189] In some embodiments, the charging management device may use any one or more of the fifth objective function, the sixth objective function, the seventh objective function, and the eighth objective function as the group objective function.

[0190] In some embodiments, the charging management device may also fuse multiple group objective functions into a single objective function as the final group objective function using a weighted algorithm. For example, the final group objective function may be obtained by weighting the fifth, sixth, seventh, and eighth objective functions.

[0191] In some embodiments, each group objective function is configured with a corresponding weight coefficient, wherein the fifth objective function is configured with a fifth weight coefficient, the sixth objective function is configured with a sixth weight coefficient, the seventh objective function is configured with a seventh weight coefficient, and the eighth objective function is configured with an eighth weight coefficient.

[0192] In this embodiment, the fifth weight coefficient is used to indicate the priority of the fifth objective function, the sixth weight coefficient is used to indicate the priority of the sixth objective function, the seventh weight coefficient is used to indicate the priority of the seventh objective function, and the eighth weight coefficient is used to indicate the priority of the eighth objective function.

[0193] The charging management device calculates the weighted sum of the group objective functions based on the fifth objective function and the fifth weight coefficient, the sixth objective function and the sixth weight coefficient, the seventh objective function and the seventh weight coefficient, and the eighth objective function and the eighth weight coefficient, and uses the weighted sum of the group objective functions as the final group objective function, which is configured to take the maximum value.

[0194] In some embodiments, the final group objective function s9 is expressed by the following formula:

[0195] model.Maximize=(s5*a5+s6*a6+s7*a7+s8*a8)

[0196] Wherein, s5 is the fifth objective function, a5 is the fifth weight coefficient, s6 is the sixth objective function, a6 is the sixth weight coefficient, s7 is the seventh objective function, a7 is the fifth weight coefficient, s8 is the eighth objective function, and a8 is the eighth weight coefficient.

[0197] In some embodiments, the priority of the seventh objective function is greater than the priority of the fifth objective function, and the priority of the fifth objective function is greater than the priority of the sixth or eighth objective function.

[0198] For example, the final group objective function s9 is expressed by the following formula:

[0199] model.Maximize=(s5*100+s6*(-1)+s7*(-100*up_LIMIT)+s8*(-1))

[0200] Since the priority of the seventh objective function is greater than that of the fifth objective function, and the priority of the fifth objective function is greater than that of the sixth or eighth objective function, the absolute value of the seventh weight coefficient, 100*up_LIMIT, is greater than the absolute value of the fifth weight coefficient, 100. The absolute value of the fifth weight coefficient, 100, is greater than the absolute value of the sixth or eighth weight coefficient, 1. Furthermore, since the seventh, sixth, and eighth objective functions are configured to take the minimum value, and the fifth objective function is configured to take the maximum value, the seventh, sixth, and eighth weight coefficients are all negative, while the fifth weight coefficient is positive.

[0201] Therefore, this embodiment uses a weighted algorithm to merge multiple group objective functions into a final group objective function, and configures the final group objective function to take the maximum value, which can make the optimization objective more in line with actual needs while achieving comprehensive optimization.

[0202] S2144. Determine the actual power allocation for each charging group based on the group constraints and group objective function after input parameters.

[0203] In this step, the charging management device can input the group constraints after one or more input parameters and the group objective function mentioned above into any suitable algorithm model such as the ortools solver to determine the actual group power allocation for each charging group.

[0204] Understandably, if the group power adjustment variable is not introduced, the algorithm model will output the actual group power allocation of all charging groups that can be solved. In this case, there may be some charging groups whose actual group power allocation has no solution. If the group power adjustment variable is introduced, the algorithm model will output the actual group power allocation and the charging power adjustment value of all charging groups. In this case, it can be ensured that the actual group power allocation of each charging group has a solution.

[0205] In some embodiments, the charging management device can input the group charging power constraint, the group total allocated power constraint, the group charging demand constraint, and the final group objective function s9 into the ortools solver to obtain the actual allocated power and charging power adjustment value of the first charging group and the actual allocated power and charging power adjustment value of the second charging group.

[0206] For example, the Ortools solver calculates that the actual power allocation for the first charging group is 55 kW, and the adjusted charging capacity for the first charging group is 2 kWh (kWh). The actual power allocation for the second charging group is 45 kW, and the adjusted charging capacity for the second charging group is 1 kWh. It can be understood that, after the adjustment, the required charging capacity for the first charging group becomes E1-2 kWh, and the required charging capacity for the second charging group becomes E2-1 kWh.

[0207] In some embodiments, please refer to Figure 5 S24 includes:

[0208] S241. Obtain the pile decision variables and pile constraints corresponding to each charging pile. The pile decision variables include the pile allocation power variables used to solve the actual allocated power of the pile.

[0209] In this step, the pile decision variables are pre-assumed variables, and each charging pile can be configured with a corresponding pile decision variable. For example, the first charging pile is configured with the pile allocation power variable Var1[ease], the second charging pile is configured with the pile allocation power variable Var2[ease], and the third charging pile is configured with the pile allocation power variable Var3[ease].

[0210] Stub constraints are conditions used to constrain stub decision variables. Those skilled in the art can set the number and type of stub constraints according to actual needs. Different stub constraints have different constraint types.

[0211] S242. Based on the pile constraint conditions and the pile constraint conditions generated with the first type of parameters after input parameters are generated;

[0212] In some embodiments, the first type of parameters includes the pile allocation power variable, the actual group allocation power, the pile charging demand information, the pile upper limit power, the pile preset lower limit power, or the pile preset upper limit power, wherein the pile preset lower limit power is the minimum power preset for the charging pile according to actual demand, and the pile preset upper limit power is the maximum power preset for the charging pile according to actual demand.

[0213] In some embodiments, the pile constraint conditions include pile charging power constraint conditions. The charging management device can obtain the first type of parameters corresponding to the pile charging power constraint conditions: pile allocation power variable, pile upper limit power, pile preset lower limit power and pile preset upper limit power, and generate the pile charging power constraint conditions after input parameters based on the pile allocation power variable, pile upper limit power, pile preset lower limit power and pile preset upper limit power.

[0214] In some embodiments, the charging power constraint condition of the charging pile is expressed by the following formula:

[0215] model.Add(min_c≤Var[ease]≤min(sn_limit,user_limit))

[0216] Where min_c is the preset lower limit power of the pile, Var[ease] is the pile allocated power variable, and min(sn_limit,user_limit) means taking the minimum value between sn_limit and user_limit, where sn_limit is the upper limit power of the pile and user_limit is the preset upper limit power of the pile.

[0217] As can be seen from this formula, the charging power constraint condition can constrain the pile allocation power variable to be greater than or equal to the preset lower limit power of the pile, and less than or equal to the minimum value between the upper limit power of the pile and the preset upper limit power of the pile.

[0218] For example, for the first charging pile, the charging power constraint condition after input parameters is expressed by the following formula:

[0219] model.Add(min_c1≤Var1[ease]≤min(sn_limit1,user_limit1))

[0220] Wherein, min_c1 is the preset lower limit power of the first charging pile, Var1[ease] is the power allocation variable of the first charging pile, sn_limit1 is the upper limit power of the first charging pile, and user_limit1 is the preset upper limit power of the first charging pile.

[0221] For the second charging pile, the charging power constraint condition after input parameters is expressed by the following formula:

[0222] model.Add(min_c2≤Var2[ease]≤min(sn_limit2,user_limit2))

[0223] Wherein, min_c2 is the preset lower limit power of the second charging pile, Var2[ease] is the power allocation variable of the second charging pile, sn_limit2 is the upper limit power of the second charging pile, and user_limit2 is the preset upper limit power of the second charging pile.

[0224] For the third charging pile, the charging power constraint condition after input parameters is expressed by the following formula:

[0225] model.Add(min_c3≤Var3[ease]≤min(sn_limit3,user_limit3))

[0226] Wherein, min_c3 is the preset lower limit power of the third charging pile, Var3[ease] is the power allocation variable of the third charging pile, sn_limit3 is the upper limit power of the third charging pile, and user_limit3 is the preset upper limit power of the third charging pile.

[0227] Therefore, this embodiment constrains the actual power allocation of each charging pile within a certain power range by using the charging power constraint condition, which can ensure that the actual power allocation of each charging pile calculated will not exceed the range, making the final actual power allocation of the pile more in line with actual needs.

[0228] In some embodiments, the pile constraint conditions include the total pile power allocation constraint conditions. The charging management device can obtain the first type of parameters corresponding to the total pile power allocation constraint conditions: the pile power allocation variable and the actual group power allocation. The device can generate the input total pile power allocation constraint conditions based on the pile power allocation variable and the actual group power allocation. For example, the charging management device can substitute the pile power allocation variable and the actual group power allocation into the total pile power allocation constraint conditions to obtain the input total pile power allocation constraint conditions.

[0229] In some embodiments, the total power distribution constraint of the piles is expressed by the following formula:

[0230] model.Add(sum(Var[ease]for ease in Var)≤up_limit)

[0231] Where sum(Var[ease]for ease in Var) means summing up the pile power allocation variables corresponding to all charging piles in the target charging group, and up_limit is the actual group power allocation of the target charging group.

[0232] As can be seen from this formula, the total power allocation constraint condition can ensure that the sum of the power allocation variables of all charging piles in the target charging group is less than or equal to the actual power allocation of the target charging group.

[0233] For example, for the first charging group, the constraint condition for the total power allocation of the charging piles after input parameters is expressed by the following formula:

[0234] model.Add(Var1[ease]+Var2[ease]+Var3[ease]≤up_limit1)

[0235] Where up_limit1 is the actual power allocated to the first charging group.

[0236] Therefore, this embodiment constrains the total actual power allocated to all charging piles in the target charging group to be less than or equal to the actual power allocated to the target charging group by using the total power allocation constraint condition. This ensures that the total actual power allocated to all charging piles in each charging group will not exceed the maximum load of the charging group.

[0237] In some embodiments, the pile decision variables also include pile power adjustment variables. The pile power adjustment variables are decision variables used to solve the charging power adjustment value of each charging pile. By introducing the pile power adjustment variables, it can be ensured that the global optimal solution of the actual power allocation of the pile is solved, and there will be no situation where there is only a local optimal solution. A local optimal solution means that the actual power allocation of some charging piles has a solution, while the actual power allocation of some charging piles has no solution.

[0238] It is understandable that when a user's charging demand is set unreasonably within a limited time and exceeds the charging range, without introducing a variable to adjust the charging pile's power, the solution may fail to meet the power requirements of all charging piles. In this case, it may lead to the problem that the actual power allocation of some charging piles is unsolvable.

[0239] In some embodiments, the pile constraint conditions include pile charging demand constraint conditions. The charging management device can obtain the first type of parameters corresponding to the pile charging demand constraint conditions: pile allocation power variable and pile power adjustment variable, and generate the pile charging demand constraint conditions after input parameters based on the pile allocation power variable and pile power adjustment variable. For example, the charging management device can substitute the pile allocation power variable and pile power adjustment variable into the pile charging demand constraint conditions to obtain the pile charging demand constraint conditions after input parameters.

[0240] In some embodiments, the charging demand constraint is expressed by the following formula:

[0241] model.Add(Var[ease]*t≥(e-e_alp[ease])*60)

[0242] Where t is the charging time required for the charging pile, e is the charging power required for the charging pile, and e_alp[ease] is the charging power adjustment variable.

[0243] As can be seen from this formula, the charging demand constraint condition can constrain the product of the charging pile power allocation variable and the charging time required to be greater than or equal to the difference between the charging power required to be charged and the charging pile power adjustment variable.

[0244] In some embodiments, the unit of charging time t is usually minutes, while the units of charging power e and charging power adjustment variable e_alp[ease] are both kilowatt-hours. Therefore, by multiplying the difference between charging power e and charging power adjustment variable e_alp[ease] by 60, the unit of charging time t can be converted from minutes to hours.

[0245] For example, for the first charging pile, the charging demand constraint after input parameters is expressed by the following formula:

[0246] model.Add(Var1[ease]*t1≥(e1-e_alp1[ease])*60)

[0247] Where Var1[ease] is the power allocation variable for the first charging pile, t1 is the charging time required for the first charging pile, e1 is the charging power required for the first charging pile, and e_alp1[ease] is the power adjustment variable for the first charging pile.

[0248] For the second charging pile, the charging demand constraint after input parameters is expressed by the following formula:

[0249] model.Add(Var2[ease]*t2≥(e2-e_alp2[ease])*60)

[0250] Where Var2[ease] is the power allocation variable for the second charging pile, t2 is the charging time required for the second charging pile, e2 is the charging power required for the second charging pile, and e_alp2[ease] is the power adjustment variable for the second charging pile.

[0251] For the third charging pile, the charging demand constraint after input parameters is expressed by the following formula:

[0252] model.Add(Var3[ease]*t3≥(e3-e_alp3[ease])*60)

[0253] Where Var3[ease] is the power allocation variable for the third charging pile, t3 is the charging time required for the third charging pile, e3 is the charging power required for the third charging pile, and e_alp3[ease] is the power adjustment variable for the third charging pile.

[0254] Therefore, this embodiment ensures that each charging pile meets its charging needs by constraining the charging capacity of each charging pile to be greater than or equal to the adjusted value of the charging capacity through the charging demand constraint.

[0255] S243. Generate the objective function for the pile based on the pile decision variables;

[0256] In this step, the pile objective function is the desired objective form expressed in terms of pile decision variables, and it is also a function of the pile decision variables. Those skilled in the art can set the number of pile objective functions according to actual needs, where different objective functions are used to achieve different optimization objectives.

[0257] In some embodiments, the target function for a charging pile includes a first target function. The charging management device accumulates the pile allocation power variable corresponding to each charging pile to obtain the first target function, which is configured to take the maximum value.

[0258] In some embodiments, the first objective function s1 is represented by the following formula:

[0259] s1=sum(Var[ease]for ease in Var)

[0260] Here, sum(Var[ease]for ease in Var) represents summing the power allocation variables of all charging piles in the target charging group.

[0261] For example, the first objective function can be expressed as follows:

[0262] s1=Var1[ease]+Var2[ease]+Var3[ease]

[0263] Therefore, this embodiment optimizes the total power distribution of the piles by using the first objective function to maximize the utilization of the actual power distribution of the group, thereby improving the utilization efficiency of the actual power distribution of the group.

[0264] In some embodiments, the target function for a charging pile includes a second target function. The charging management device averages the power allocation variables of the charging piles to obtain the average power allocation value. The absolute value of the power allocation variable of each charging pile is then subtracted from the average power allocation value to obtain the power allocation deviation of each charging pile. The power allocation deviations of each charging pile are accumulated to obtain the second target function, which is configured to take the minimum value.

[0265] In some embodiments, the second objective function s2 is expressed as follows:

[0266] s2=sum(diff3[ease]for ease in diff3)

[0267] model.Add=(var_s==sum(Var[ease]for ease in Var))

[0268] model.AddDivisionEquality=(mean3,var_s,int(len(Var)))

[0269] model.Add(diff33[ease]==Var[ease]-mean3)

[0270] model.AddAbsEquality(diff3[ease],diff33[ease])

[0271] Where Var_s is the sum of the pile allocation power variables corresponding to all charging piles in the target charging group, mean3 is the average pile allocation power, diff33[ease] is the difference between the pile allocation power corresponding to each charging pile and the average pile allocation power, diff3[ease] is the pile allocation power deviation corresponding to each charging pile, and sum(diff3[ease]for easein diff3) means summing the pile allocation power deviations corresponding to all charging piles in the target charging group.

[0272] For example, the second objective function can be expressed as follows:

[0273] s2=|Var1[ease]-Var123[ease]|+|Var2[ease]-Var123[ease]|+|Var3[ease]-Var123[ease]|

[0274]

[0275] Therefore, this embodiment optimizes the pile power distribution deviation by minimizing the deviation through the second objective function, which can maximize the satisfaction of the power demand of each charging pile, thereby improving the rationality of the power allocation of the actual power distribution of the group.

[0276] In some embodiments, the target function for a charging pile includes a third target function. The charging management device accumulates the pile power adjustment variable corresponding to each charging pile to obtain the third target function, which is configured to take the minimum value.

[0277] In some embodiments, the third objective function s3 is expressed as follows:

[0278] s3=sum(e_alp[ease]for ease in e_alp)

[0279] Here, sum(e_alp[ease]for ease in e_alp) means summing up the pile power adjustment variables corresponding to all charging piles in the target charging group.

[0280] For example, the third objective function can be expressed as follows:

[0281] s3=e_alp1[ease]+e_alp2[ease]+e_alp3[ease]

[0282] Therefore, this embodiment optimizes the total adjustment power of the charging piles to the minimum by using the third objective function, which can minimize the power adjustment of each charging pile in each charging group while ensuring that the actual power allocation of the charging piles has a solution.

[0283] In some embodiments, the target function for a charging pile includes a fourth target function. The optimization objective of the fourth target function is to minimize the pile power adjustment deviation. The charging management device averages the pile power adjustment variables to obtain the pile power adjustment mean. The pile power adjustment variable corresponding to each charging pile is subtracted from the pile power adjustment mean, and the absolute value is taken to obtain the pile power adjustment deviation corresponding to each charging pile. The pile power adjustment deviations corresponding to each charging pile are accumulated to obtain the fourth target function, which is configured to take the minimum value.

[0284] In some embodiments, the fourth objective function s4 is expressed as follows:

[0285] s4=sum(diff4[ease]for ease in diff4)

[0286] model.Add=(ealp_s==sum(e_alp[ease]for ease in e_alp))

[0287] model.AddDivisionEquality=(mean4,ealp_s,int(len(e_alp)))

[0288] model.Add(diff44[ease]==e_alp[ease]-mean4)

[0289] model.AddAbsEquality(diff4[ease],diff44[ease])

[0290] Where, ealp_s is the sum of the pile power adjustment variables corresponding to all charging piles in the target charging group, mean4 is the average pile power adjustment, diff44[ease] is the difference between the pile power adjustment variable and the average pile power adjustment for each charging pile, diff4[ease] is the pile power adjustment deviation for each charging pile, and sum(diff4[ease]forease in diff4) means summing the group power adjustment deviations corresponding to all charging piles in the target charging group.

[0291] For example, the fourth objective function can be expressed as follows:

[0292] s4=|e_alp1[ease]-e_alp123[ease]|+|e_alp2[ease]-e_alp123[ease]|+|e_alp3[ease]-e_alp123[ease]|

[0293]

[0294] Therefore, this embodiment optimizes the pile power adjustment deviation by using the fourth objective function to minimize the deviation, which can maximize the satisfaction of the charging power demand of each charging pile while ensuring that the actual power allocation of the pile has a solution.

[0295] In some embodiments, the charging management device may use any one or more of the first objective function, the second objective function, the third objective function, and the fourth objective function as the charging objective function.

[0296] In some embodiments, the charging management device can also fuse multiple pile objective functions into a single objective function as the final group objective function using a weighted algorithm. For example, the final pile objective function can be obtained by weighting the first objective function, the second objective function, the third objective function, and the fourth objective function.

[0297] In some embodiments, each piling objective function is configured with a corresponding weight coefficient, wherein the first objective function is configured with a first weight coefficient, the second objective function is configured with a second weight coefficient, the third objective function is configured with a third weight coefficient, and the fourth objective function is configured with a fourth weight coefficient.

[0298] The first weighting coefficient is used to indicate the priority of the first objective function, the second weighting coefficient is used to indicate the priority of the second objective function, the third weighting coefficient is used to indicate the priority of the third objective function, and the fourth weighting coefficient is used to indicate the priority of the fourth objective function.

[0299] The charging management device calculates the weighted sum of the pile objective functions based on the first objective function and the first weight coefficient, the second objective function and the second weight coefficient, the third objective function and the third weight coefficient, and the fourth objective function and the fourth weight coefficient, and uses the weighted sum of the pile objective functions as the final pile objective function. The final pile objective function is configured to take the maximum value.

[0300] In some embodiments, the final pile objective function s10 is expressed by the following formula:

[0301] model.Maximize=(s1*a1+s2*a2+s3*a3+s4*a4)

[0302] Wherein, s1 is the first objective function, a1 is the first weight coefficient, s2 is the second objective function, a2 is the second weight coefficient, s3 is the third objective function, a3 is the third weight coefficient, s4 is the fourth objective function, and a4 is the fourth weight coefficient.

[0303] In some embodiments, the priority of the third objective function is greater than the priority of the first objective function, and the priority of the first objective function is greater than the priority of the second or fourth objective function.

[0304] For example, the final pile objective function s10 is expressed by the following formula:

[0305] model.Maximize=(s1*100+s2*(-1)+s3*(-100*up_limit)+s4*(-1))

[0306] Since the priority of the third objective function is greater than that of the first objective function, and the priority of the first objective function is greater than that of the second or fourth objective function, the absolute value of the third weight coefficient, 100 * up_limit, is greater than the absolute value of the first weight coefficient, 100. The absolute value of the first weight coefficient, 100, is greater than the absolute value of the second weight coefficient, 1 or the absolute value of the second weight coefficient, 1. Furthermore, since the third, second, and fourth objective functions are configured to take the minimum value, and the first objective function is configured to take the maximum value, the third, second, and fourth weight coefficients are all negative, while the first weight coefficient is positive.

[0307] Therefore, this embodiment uses a weighted algorithm to merge multiple pile objective functions into a final pile objective function, and configures the final pile objective function to take the maximum value, which can make the optimization objective more in line with actual needs while achieving comprehensive optimization.

[0308] S244. Determine the actual power allocation for each charging pile based on the pile constraint conditions and pile objective function after input parameters.

[0309] In this step, the charging management device can input the pile constraint conditions after one or more input parameters and the pile objective functions mentioned above into any suitable algorithm model such as the ortools solver to determine the actual power allocation of each charging pile.

[0310] Understandably, if the charging pile power adjustment variable is not introduced, the algorithm model will output the actual power allocation of all charging piles that can be solved. In this case, there may be some charging piles whose actual power allocation has no solution. If the charging pile power adjustment variable is introduced, the algorithm model will output the actual power allocation of all charging piles and the charging pile power adjustment value. In this case, it can be ensured that the actual power allocation of each charging pile has a solution.

[0311] In some embodiments, the charging management device can input the charging power constraint, the total power allocation constraint, the charging demand constraint, and the final objective function s10 of the charging pile into the ortools solver to obtain the actual power allocation and power adjustment value of the first charging pile, the actual power allocation and power adjustment value of the second charging pile, and the actual power allocation and power adjustment value of the third charging pile.

[0312] For example, the Ortools solver calculates that the actual power allocated to the first charging pile is 18 kW, and the adjusted power consumption value is 0.7 kWh; the actual power allocated to the second charging pile is 19 kW, and the adjusted power consumption value is 0.8 kWh; the actual power allocated to the third charging pile is 17 kW, and the adjusted power consumption value is 0.5 kWh. This means that after the power consumption adjustment, the required power consumption for the first charging pile becomes e1 - 0.7 kWh, the second charging pile becomes e2 - 0.8 kWh, and the third charging pile becomes e3 - 0.5 kWh.

[0313] This application provides a charging power distribution device. Please refer to [link / reference]. Figure 6 The charging power distribution device 600 includes a first acquisition module 61, a first determination module 62, a second determination module 63, and a third determination module 64.

[0314] The first acquisition module 61 is used to acquire the charging demand information of each charging pile in the target charging group, the target charging group includes at least two charging piles. The first determination module 62 is used to determine the actual power allocation of the target charging group, the actual power allocation is the highest power allocated to the target charging group. The second determination module 63 is used to determine the upper limit power of each charging pile in the target charging group. The third determination module 64 is used to determine the actual power allocation of each charging pile based on the actual power allocation, the charging demand information and the upper limit power.

[0315] In some embodiments, please refer to Figure 7 The third determining module 64 includes a first acquiring unit 641, a first generating unit 642, a second generating unit 643, and a first determining unit 644.

[0316] The first acquisition unit 641 is used to acquire the pile decision variables and pile constraint conditions corresponding to each charging pile. The pile decision variables include the pile allocation power variable used to solve the actual allocated power of the pile. The first generation unit 642 is used to generate the pile constraint conditions after input parameters according to the pile constraint conditions and the parameters corresponding to the constraint condition type of the pile constraint conditions. The second generation unit 643 is used to generate the pile objective function according to the pile decision variables. The first determination unit 644 is used to determine the actual allocated power of each charging pile according to the pile constraint conditions after input parameters and the pile objective function.

[0317] In some embodiments, please refer to Figure 8 The first determining module 62 includes a second obtaining unit 621, a second determining unit 622, a third determining unit 623 and a fourth determining unit 624.

[0318] The second acquisition unit 621 is used to acquire the upper limit power of the charging station and the charging demand information of each charging pile in each charging group in the charging station. The second determination unit 622 is used to determine the group charging demand information of each charging group in the charging station based on the charging demand information of each charging pile in each charging group. The third determination unit 623 is used to determine the upper limit power of each charging group in the charging station. The fourth determination unit 624 is used to determine the actual group allocation power of each charging group based on the upper limit power of the station, the group charging demand information and the upper limit power of the group.

[0319] In some embodiments, please refer to Figure 9 The second determining module 63 includes a third acquiring unit 631, a judging unit 632, a fifth determining unit 633, and a sixth determining unit 634.

[0320] The third acquisition unit 631 is used to acquire the design power of each charging pile and the upper limit power of the charging vehicle corresponding to each charging pile. The judgment unit 632 is used to determine whether the charging time of the charging vehicle is less than the preset time. The fifth determination unit 633 is used to determine the lower limit power of the charging vehicle and the design power of the charging pile corresponding to the charging vehicle as the upper limit power of the charging pile when the charging time of the charging vehicle is less than the preset time. The sixth determination unit 634 is used to acquire the reported power of the charging vehicle when the charging time of the charging vehicle is greater than or equal to the preset time, and determine the required power of the charging vehicle based on the reported power of the charging vehicle and the preset compensation threshold. It also determines the lower limit power of the charging pile as the minimum of the required power of the charging vehicle, the upper limit power of the charging vehicle, and the design power of the charging pile corresponding to the charging vehicle.

[0321] It should be noted that the above-described charging power distribution device can execute the charging power distribution method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in the embodiments of the charging power distribution device can be found in the charging power distribution method provided in the embodiments of this application.

[0322] This application provides an embodiment of an electronic device, which can be a charging management device as described above. Please refer to... Figure 10 The electronic device 1000 includes one or more processors 101 and memory 102. Figure 10 Take a processor 101 as an example.

[0323] Processor 101 and memory 102 can be connected via a bus or other means. Figure 10 Taking the example of a connection between China and Israel via a bus.

[0324] The memory 102, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the charging power allocation method in the embodiments of this application. The processor 101 executes various functional applications and data processing of the charging power allocation device by running the non-volatile software programs, instructions, and modules stored in the memory 102, thereby realizing the functions of the charging power allocation method provided in the above method embodiments and the various modules or units in the above device embodiments.

[0325] Memory 102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 102 includes memory remotely located relative to processor 101, and these remote memories may be connected to processor 101 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0326] The program instructions / modules are stored in the memory 102 and, when executed by one or more processors 101, execute the charging power allocation method in any of the above method embodiments.

[0327] This application also provides a non-volatile computer storage medium storing computer-executable instructions, which are executed by one or more processors, for example... Figure 10 One of the processors 101 can enable the one or more processors to execute the charging power distribution method in any of the above method embodiments.

[0328] This application also provides a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium. The computer program includes program instructions that, when executed by an electronic device, cause the electronic device to perform any of the charging power distribution methods described above.

[0329] The device or equipment embodiments described above are merely illustrative. The unit modules described as separate components may or may not be physically separate. The components shown as module units may or may not be physical units; that is, they may be located in one place or distributed across multiple network module units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0330] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0331] Finally, it should be noted that this application can be implemented in many different forms and is not limited to the embodiments described in this specification. These embodiments are not intended to impose additional limitations on the content of this application; the purpose of providing these implementation methods is to make the disclosure of this application more thorough and comprehensive. Furthermore, within the framework of this application, the above-mentioned technical features can be combined with each other, and there are many other variations of different aspects of this application as described above, all of which are considered to be within the scope of this specification. Moreover, those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A charging power distribution method, characterized in that, include: Obtain the charging demand information of each charging pile in the target charging group, wherein the target charging group includes at least two charging piles, and the charging demand information includes the charging time and the charging power required for the charging pile. Determine the actual power allocated to the target charging group, where the actual power allocated to the target charging group is the highest power allocated to the target charging group; Determine the maximum power output of each charging pile within the target charging group; The actual power allocation for each charging pile is determined based on the charging demand information, the actual power allocation for the group, and the upper limit power of the pile, including: Obtain the pile decision variables and pile constraints corresponding to each charging pile. The pile decision variables include pile allocation power variables and pile power adjustment variables used to solve the actual allocated power of the pile. The pile constraints include pile charging demand constraints. The pile constraint conditions are generated based on the pile constraint conditions and the first type of parameters, including: obtaining the first type of parameters corresponding to the pile charging demand constraint conditions: the required charging time of the pile, the required charging power of the pile, and the pile power adjustment variable; generating the pile charging demand constraint conditions based on the required charging time of the pile, the required charging power of the pile, and the pile power adjustment variable, wherein the pile charging demand constraint conditions are used to constrain the product of the pile power allocation variable and the required charging time of the pile to be greater than or equal to the difference between the required charging power of the pile and the pile power adjustment variable; Generate the pile objective function based on the pile decision variables; The actual power allocation for each charging pile is determined based on the pile constraint conditions after input parameters and the pile objective function.

2. The method according to claim 1, characterized in that, The pile constraint conditions include pile charging power constraint conditions. The first type of parameters also includes a preset lower limit power and a preset upper limit power for the pile. The pile constraint conditions generated based on the pile constraint conditions and the first type of parameters include: Obtain the first type of parameters corresponding to the charging power constraint of the pile: the pile power allocation variable, the pile upper limit power, the pile preset lower limit power and the pile preset upper limit power; Based on the pile power allocation variable, the pile upper limit power, the pile preset lower limit power, and the pile preset upper limit power, the pile charging power constraint condition is generated after input parameters are generated. The pile charging power constraint condition is used to constrain the pile power allocation variable to be greater than or equal to the pile preset lower limit power, and less than or equal to the minimum value of the pile upper limit power and the pile preset upper limit power.

3. The method according to claim 1, characterized in that, The pile constraint conditions include the total distributed power constraint conditions for the piles, and the pile constraint conditions generated based on the pile constraint conditions and the first type of parameters after generating the input parameters include: Obtain the first type of parameters corresponding to the total power distribution constraint of the piles: the power distribution variable of the piles and the actual power distribution of the group; Based on the pile allocation power variables and the actual group allocation power, the total pile allocation power constraint condition is generated after input parameters. The total pile allocation power constraint condition is used to constrain the sum of the pile allocation power variables corresponding to all charging piles to be less than or equal to the actual group allocation power.

4. The method according to claim 1, characterized in that, The pile objective function includes a first objective function and a second objective function, and generating the pile objective function based on the pile decision variables includes: The pile allocation power variable corresponding to each charging pile is summed to obtain the first objective function, which is configured to take the maximum value. The average value of the pile distribution power is obtained by averaging the pile distribution power variables. The absolute value of the pile allocation power variable is obtained by subtracting the average pile allocation power from the pile allocation power variable corresponding to each charging pile and taking the absolute value. The power allocation deviation of each charging pile is accumulated to obtain the second objective function, which is configured to take the minimum value.

5. The method according to claim 4, characterized in that, The pile decision variables also include pile power adjustment variables, and the pile objective function also includes a third objective function and a fourth objective function. Generating the pile objective function based on the pile decision variables includes: The third objective function is obtained by summing up the pile power adjustment variables corresponding to each charging pile, and the third objective function is configured to take the minimum value. The average value of the pile power adjustment variable is obtained by averaging the pile power adjustment variables. Subtract the average value of the pile power adjustment from the pile power adjustment variable corresponding to each charging pile, and then take the absolute value to obtain the pile power adjustment deviation corresponding to each charging pile. The fourth objective function is obtained by summing up the pile power adjustment deviations corresponding to each charging pile, and the fourth objective function is configured to take the minimum value.

6. The method according to claim 5, characterized in that, Also includes: Based on the first objective function and the first weight coefficient, the second objective function and the second weight coefficient, the third objective function and the third weight coefficient, and the fourth objective function and the fourth weight coefficient, a weighted sum of objective functions is calculated, and the weighted sum of objective functions is used as the final piling objective function.

7. The method according to claim 1, characterized in that, The determination of the actual power allocation for the target charging group includes: Obtain the maximum power output of the charging station; The group charging demand information of each charging group in the charging station is determined based on the pile charging demand information of each charging pile in each charging group. Determine the maximum power limit for each charging group within the charging station; The actual power allocation for each charging group is determined based on the station's maximum power capacity, the group charging demand information, and the group's maximum power capacity.

8. The method according to claim 7, characterized in that, Determining the maximum power output of each charging pile within the target charging group includes: Obtain the design power of each charging pile and the upper limit of charging power for the vehicle corresponding to each charging pile; Determine whether the charging time of the vehicle being charged is less than a preset time; If it is less than the preset time, the minimum value between the upper limit charging power of the charging vehicle and the pile design power of the charging pile corresponding to the charging vehicle is determined to be the upper limit charging power of the charging pile. If the power is greater than or equal to the preset duration, the reported power of the charging vehicle is obtained. Based on the reported power of the charging vehicle and the preset compensation threshold, the required power of the charging vehicle is determined, and the minimum value of the required power of the charging vehicle, the upper limit power of charging, and the design power of the charging pile corresponding to the charging vehicle is determined as the upper limit power of the charging pile.

9. An electronic device, characterized in that, Includes at least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores commands that can be executed by the at least one processor to enable the at least one processor to perform the charging power distribution method as described in any one of claims 1 to 8.

10. A non-volatile computing storage medium, characterized in that, The non-volatile computer storage medium stores computer-executable commands for causing the electronic device to perform the charging power distribution method as described in any one of claims 1 to 8.

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