New energy charging pile power distribution method and system for multiple charging guns

Abstract

The invention relates to the technical field of charging pile power distribution, in particular to a new energy charging pile power distribution method and system for multiple charging guns, and the method specifically comprises the steps: carrying out the priority weight distribution based on time, and enabling a first-arrival user to preferentially enjoy higher charging power according to a first-arrival first-service principle; an electric vehicle demand characterization factor is calculated according to the electric vehicle residual electric quantity, the electric vehicle with low electric quantity and urgently needing to be charged obtains certain electric energy, and the charging efficiency is improved; determining an expected time allocation weight of each charging pile based on the power change during charging; a suppression factor is introduced based on a total output power change trend prediction result to deal with total output power change in advance; comprehensively analyzing to adjust the distribution power of the charging pile in real time; the waiting time of the user is reduced through dynamic allocation, and efficient utilization of total output power, improvement of user experience and optimization of operation management of the charging station are realized.

Description

Technical Field

[0001] The present application relates to the technical field of charging pile power distribution, and specifically to a new energy charging pile power distribution method and system for multiple charging guns. Background Art

[0002] With the acceleration of the global energy transition, new energy vehicles are experiencing unprecedented development opportunities, with market ownership experiencing explosive growth. Charging stations, as critical infrastructure for new energy vehicles, are becoming increasingly important. However, existing charging station technology faces numerous challenges in simultaneously charging multiple vehicles, particularly in power distribution. More efficient and intelligent solutions are urgently needed to improve charging efficiency and user experience.

[0003] Traditional charging piles mostly use a single-pole design. Even in a few multi-pole charging piles, their power distribution is relatively simple, typically an even distribution or a fixed ratio. This distribution method cannot dynamically adjust to the actual charging needs of the electric vehicle and the battery status, resulting in low charging efficiency and failure to fully utilize the charging pile's performance. For example, during peak charging periods, when multiple vehicles are charging simultaneously, improper power distribution may cause some vehicles to charge too slowly or even fail to meet basic charging requirements, seriously affecting the charging experience and acceptance of new energy vehicles. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a new energy charging pile power distribution method and system for multiple charging guns. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for allocating power to a new energy charging pile with multiple charging guns, the method comprising the following steps:

[0006] Real-time collection of the total output power of the distribution cabinet at the charging station and the output power allocated to each charging pile by the distribution cabinet, as well as the actual remaining power of each charging electric vehicle connected to each charging pile;

[0007] At the current moment, the priority weight of each charging pile is set based on the usage time of each charging pile; the vehicle demand characterization factor of each charging pile is calculated based on the actual remaining power of all charging electric vehicles connected to each charging pile; based on the difference in the output power of the charging pile corresponding to the time when each electric vehicle started charging and the current moment, the change in the expected charging time of each electric vehicle is analyzed to determine the expected time allocation weight of each charging pile;

[0008] The total output power of the distribution cabinets at multiple future moments is predicted based on the total output power of the distribution cabinets at historical moments. The suppression factors of all charging piles at the current moment are calculated based on the difference between the total output power prediction values ​​and the total output power of the distribution cabinets at the current moment, as well as the degree of distribution disorder of the total output power prediction values.

[0009] The allocated power of each charging pile at the current moment is determined based on the total output power of the distribution cabinet at the current moment, the priority weight, the electric vehicle demand characterization factor, the inhibition factor and the time expected allocation weight; if the current moment is the preset adjustment moment, the output power of each charging pile is allocated according to the allocated power.

[0010] In one embodiment, the actual remaining power is the product of the remaining percentage of the charging vehicle and the total capacity of the battery of the charging vehicle.

[0011] In one embodiment, the process of obtaining the priority weight is as follows:

[0012] The priority weights are set to M+1 levels from 0 to M, where M is equal to the number of charging piles. For the charging piles currently in use, the current continuous usage time of each charging pile is obtained, and all the charging piles are arranged from large to small according to the current continuous usage time. The priority weight of the charging pile with the longest current continuous usage time is set to the highest priority weight M, and the priority weight is assigned to each charging pile in descending order of arrangement. The priority weight of the charging piles that are not currently in use is set to 0.

[0013] In one embodiment, the process of obtaining the tram demand characterization factor is as follows:

[0014] The average of the normalized values ​​of the actual remaining power of the charging electric vehicles connected to all the charging guns of each charging pile is calculated, and the difference between the natural number 1 and the average is used as the electric vehicle demand characterization factor of each charging pile.

[0015] In one embodiment, the expression of the time expectation allocation weight is:

[0016]

[0017] Where Y represents the expected time allocation weight of the current charging pile at the current moment; n is the number of charging guns included in the current charging pile; Pv v Indicates the charging time of the electric vehicle connected to the vth charging gun of the current charging pile at the current moment; Ms v Tb represents the estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile at the current moment; vIndicates the estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile when charging begins.

[0018] In one embodiment, the inhibitory factor is expressed as:

[0019]

[0020] Among them, U represents the suppression factor of all charging piles at the current moment; μ represents the average value of the difference between the total output power prediction value of all the future moments and the total output power of the distribution cabinet at the current moment; δ represents the variance of the total output power prediction value of all the future moments; norm() is the normalization function.

[0021] In one embodiment, the process of obtaining the allocated power is as follows:

[0022] Calculate the final allocation weight Mb of the i-th charging pile at the current moment i , Mb i The expression is: Mb i =b+Rc i +Hg i +U×Q i , where b represents the preset initial allocation weight of any charging pile; Rc i Hg is the normalized value of the priority weight of the i-th charging pile at the current moment; i represents the normalized value of the electric vehicle demand characterization factor of the i-th charging pile at the current moment; U represents the inhibition factor of all charging piles at the current moment; Q i represents the normalized value of the expected time allocation weight of the i-th charging pile at the current moment;

[0023] The allocated power of each charging pile at the current moment is determined based on the final allocation weight and the total output power of the distribution cabinet at the current moment.

[0024] In one embodiment, the allocated power of each charging pile at the current moment is: the product of the normalized value of the final allocation weight of each charging pile at the current moment and the total output power of the distribution cabinet.

[0025] In one embodiment, if the current moment is the preset adjustment moment, the output power of each charging pile is distributed by the distributed power, specifically:

[0026] After every preset time period, the output power of each charging pile is redistributed by the power distribution method; wherein, when a new electric vehicle is charged at any charging pile, the output power of each charging pile is also redistributed.

[0027] On the second aspect, an embodiment of the present application also provides a new energy charging pile power distribution system for multiple charging guns, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above methods are implemented.

[0028] The embodiments of the present application have at least the following beneficial effects:

[0029] This application achieves efficient utilization of total output power, meets the personalized charging needs of electric vehicles, improves user experience, and optimizes charging station operation and management through precise dynamic power allocation, providing a more intelligent, efficient, and reliable solution for charging new energy vehicles.

[0030] This application introduces multiple allocation weights, takes into account multiple practical needs of electric vehicle charging, performs adaptive power allocation, avoids average allocation problems, improves charging efficiency, and ensures that electric vehicles receive appropriate charging services. Among them, the time-based priority weight allocation follows the first-come, first-served principle, so that first-arriving users can enjoy higher charging power first, which is in line with users' daily usage habits and reduces waiting time. The electric vehicle demand characterization factor is calculated based on the remaining power of the electric vehicle, so that electric vehicles with low power and in urgent need of charging can obtain a certain amount of power first, improving charging efficiency, ensuring the normal use of new energy vehicles, and reducing the risk of users being unable to travel due to insufficient power. The time expectation allocation weight of each charging pile is determined based on the power change during charging. The inhibition factor is introduced based on the prediction result of the total output power change trend to respond to the total output power change in advance, enhance the stability of the charging process, and avoid charging interruptions or delays caused by fluctuations in the total output power of the distribution cabinet or changes in the status of other charging piles. The user waiting time is reduced through dynamic allocation, allowing users to accurately estimate the charging completion time and reasonably arrange their trips. The total output power change is predicted and the allocation weight is adjusted to enhance charging stability and reduce the risk of interruption or delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0032] Figure 1 A flowchart of the steps of a power distribution method for a new energy charging pile with multiple charging guns provided in one embodiment of the present application;

[0033] Figure 2 Schematic diagram of the process of obtaining tram demand characterization factors. DETAILED DESCRIPTION

[0034] In order to further illustrate the technical means and effects adopted by this application to achieve the predetermined invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, describes in detail the specific implementation method, structure, features and effects of the new energy charging pile power distribution method and system for multiple charging guns proposed in this application. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0035] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0036] The specific scheme of the power distribution method and system for new energy charging piles with multiple charging guns provided by this application is described in detail below with reference to the accompanying drawings.

[0037] See also Figure 1 , which shows a flowchart of a method for allocating power to a new energy charging pile with multiple charging guns according to an embodiment of the present application. The method includes the following steps:

[0038] Step S1 : collecting in real time the total output power of the distribution cabinet of the charging station and the output power allocated by the distribution cabinet to each charging pile, as well as the actual remaining power of each charging electric vehicle connected to each charging pile.

[0039] Obtain the number of charging piles in the charging station and monitor the total output power of the distribution cabinet of the charging station in real time. The total output power is the total amount of charging power that the distribution cabinet can provide to all charging piles; at the same time, obtain the output power allocated to each charging pile by the distribution cabinet in real time.

[0040] Each charging station contains multiple charging guns, allowing multiple vehicles to be charged simultaneously. For any vehicle connected to a charging gun in use, the remaining percentage of power is obtained in real time. Combined with the vehicle's total battery capacity, the actual remaining power at each moment is determined. For example, if the vehicle's total battery capacity is A kWh and the remaining percentage at the current moment is 30%, the vehicle's actual remaining power at that moment is A*30% kWh.

[0041] Among them, for the data collection frequency of various types of data, in the embodiment of the present application, the collection frequency is set to be collected once every ten minutes. As other embodiments of the present application, the implementer can set the data collection frequency according to actual conditions.

[0042] Step S2: at the current moment, set the priority weight of each charging pile based on the usage time of each charging pile; calculate the vehicle demand characterization factor of each charging pile based on the actual remaining power of all charging vehicles connected to each charging pile; analyze the change of the expected charging time of each vehicle based on the difference in output power of the charging pile corresponding to the starting time of each vehicle and the current moment, and determine the time expectation allocation weight of each charging pile.

[0043] The total output power limit of the distribution cabinet also limits the output power of the charging piles, causing the output power of these charging piles to restrict each other. When the total output power is insufficient, the excessive power of one charging pile will limit the power of other charging piles, affecting charging speed. Therefore, it is necessary to allocate power to each charging pile so that the resultant allocation meets the usage requirements of each charging pile as much as possible.

[0044] (1) First, obtain the maximum output power of each charging pile, and calculate the sum of the maximum output powers of all charging piles in the charging station at the current moment, which is recorded as the power sum P; if the power sum P is less than or equal to the total output power of the distribution cabinet, it means that each charging pile can use the maximum output power for charging. Conversely, if the power sum P is greater than the total output power of the distribution cabinet, it is necessary to dynamically allocate according to the needs of each charging pile to meet the needs of each charging user as much as possible.

[0045] (2) In the case where the power sum value P is greater than the total output power, this application first sets an initial allocation weight for each charging pile. This allocation weight is used to determine the power allocated to each charging pile by the distribution cabinet. In this application, the initial allocation weight of each charging pile is set to 1, that is, when all charging piles are not in use, the power allocated to all charging piles is the same. The allocation weight of each charging pile can be adjusted according to the real-time usage of the charging pile, thereby adaptively adjusting the power allocation result of the charging pile.

[0046] Furthermore, priority weights are assigned to each charging pile according to the order in which they are used, that is, according to the principle of first come first served, priority weights are set for the charging power of each charging pile, and the allocated power of the corresponding charging pile can be dynamically allocated according to the priority weights.

[0047] Specifically, assuming the number of charging piles is M, the priority weights set in this application are 0 to M, with a total of M+1 levels. Priority weights are dynamically assigned based on the time the charging piles are used or reserved. First, for the charging piles currently in use, the current continuous use time of each charging pile is obtained, wherein at least one charging gun of each charging pile is in use during the current continuous use time. Then, all charging piles are arranged from large to small according to the current continuous use time, and the priority weight of the charging pile with the longest current continuous use time is set to the highest priority weight M. Priority weights are assigned to each charging pile in descending order of arrangement; if the charging pile is not in use at the current moment, the priority weight of the unused charging pile is set to 0. For example, suppose there are five charging piles, namely A, B, C, D and E, among which A is used for 1 hour, B is used for 50 minutes, and B is used for 30 minutes, and D and E are not used. Then M=5, and the priority weights of A, B and C are 5, 4 and 3 respectively, and the priority weights of D and E are both 0.

[0048] Normalize the priority weight of each charging pile at the current moment. The normalization method used in this application is: where Rc i represents the normalized value of the priority weight of the i-th charging pile at the current moment, R i 、R j They represent the priority weights of the i-th and j-th charging piles at the current moment, and M represents the number of charging piles.

[0049] (3) Then, since some electric vehicles have less power, they may need to be charged urgently instead of fully charged before going. Therefore, the remaining power of the electric vehicles corresponding to the charging piles can be allocated, and the electric vehicles with less power can be charged first.

[0050] Based on the above analysis, the electric vehicle demand characterization factor of each charging pile at the current moment is calculated as follows:

[0051]

[0052] Among them, H i represents the electric vehicle demand characterization factor of the i-th charging pile at the current moment, n i Indicates the number of charging guns contained in the i-th charging pile, L i,u It represents the normalized value of the actual remaining power of the charging vehicle connected to the u-th charging gun of the i-th charging pile at the current moment.

[0053] In the embodiment of this application, the normalization method for the actual remaining power is to obtain the maximum value of the total battery capacity of all charging vehicles connected to all charging piles at the current moment, and use the ratio of the actual remaining power of each charging vehicle to the maximum value as the normalized value of the actual remaining power of the charging vehicle. Implementers may also use other methods to normalize the actual remaining power, and this application does not impose specific limitations.

[0054] The lower the actual remaining power of the electric vehicle charged on the corresponding charging gun of the required charging pile, the greater the electric vehicle demand representation factor of the charging pile.

[0055] Furthermore, the maximum and minimum method is used to normalize the vehicle demand characterization factors of all charging piles at the current moment. The implementer may also use other normalization methods to normalize the vehicle demand characterization factors of the charging piles. This application does not impose any specific restrictions.

[0056] (4) Analyze the relationship between each preset charging time and the actual charging time, and analyze the completion results based on the current allocation results, so as to dynamically allocate so that each user can complete the charging within the expected time, reducing the user's waiting time and improving the user experience.

[0057] In order to enable users to clearly understand the charging time of the tram and allocate their time more conveniently, most existing trams will display the estimated charging time when charging. However, due to changes in load and the operating status of other charging piles, the charging power of the charging gun allocated to the charging pile will change. Therefore, in order to reduce the actual charging time exceeding the initial preset charging time due to such changes, it is necessary to calculate the expected time allocation weight of each charging pile at the current moment based on the sum of the current charging time and the current expected charging time, and the relationship with the initial preset charging time, so as to avoid or reduce the actual excess time. The expression of the expected time allocation weight is:

[0058]

[0059] Where Y represents the expected time allocation weight of the current charging pile at the current moment; n is the number of charging guns included in the current charging pile; Pv v Indicates the charging time of the electric vehicle connected to the vth charging gun of the current charging pile at the current moment; Ms v The estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile at the current moment is recorded as the current estimated charging time. Specifically, it is the estimated full charging time determined based on the output power of the current charging pile at the current moment and the actual power demand of the electric vehicle at the current moment; Tb vIt indicates the estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile when charging begins. This is recorded as the initial estimated charging time. Specifically, it is the estimated full charging time determined based on the charging pile power when the user first arrives and uses the charging gun, and the actual power demand of the charging electric vehicle at the time of initial arrival.

[0060] The actual power demand of each tram at the current moment is the difference between the total battery capacity of each tram at the current moment and the actual remaining power.

[0061] When the sum of the current charging time and the current preset remaining time is greater than the initial preset time required to complete charging, the time expected allocation weight corresponding to the charging pile will be greater. v +Ms v |-Tb v If it is a non-positive value, just record it as 0.

[0062] Normalize the expected time allocation weights of all charging piles at the current moment. This application uses the following expression for normalization: Where Q i is the normalized value of the expected time allocation weight of the i-th charging pile at the current moment, Y i 、Y j are the expected time allocation weights of the i-th and j-th charging piles at the current moment, respectively, and M is the number of charging piles. Implementers may also use other normalization methods to normalize the expected time allocation weights of all charging piles, and this application does not impose any specific restrictions.

[0063] Step S3: predict the total output power of the distribution cabinet at multiple future moments based on the total output power of the distribution cabinet at historical moments; calculate the suppression factor of all charging piles at the current moment based on the difference between all the total output power prediction values ​​and the total output power of the distribution cabinet at the current moment, as well as the degree of distribution disorder of all the total output power prediction values.

[0064] This application predicts the changing trend of the total output power of the distribution cabinet. If the total output power shows an increasing trend in the prediction result, then under the current situation, we can appropriately favor customers corresponding to charging piles that are expected to time out or have already timed out. On the contrary, if the total output power shows a decreasing trend, then if the allocation is carried out according to the above method, the charging piles that have not timed out now may time out, which will result in not meeting the needs of any user.

[0065] Therefore, this application obtains the time expectation distribution weight suppression factor based on the prediction result of the total output power change trend of the distribution cabinet. The specific method is as follows:

[0066] First, obtain the total output power data of the distribution cabinet collected within the historical x days before the current moment, and record the sequence composed of them in chronological order as the historical total output power sequence of the current moment; use the total output power sequence as the input of the existing ARIMA prediction algorithm to predict the total output power of the next a moments, and calculate the variance δ of the total output power prediction value of these a moments, and calculate the difference between the total output power prediction value of each future moment and the total output power of the distribution cabinet at the current moment. For the values ​​of x and a, in the embodiment of the present application, the value of x is set to 1, and the value of a is set to 6, that is, the total output power within the next 1 hour is predicted. In other embodiments of the present application, the implementer can set the values ​​of x and a according to the actual situation. Among them, the ARIMA prediction algorithm is a well-known technology, and the specific process will not be repeated.

[0067] It should be noted that for the prediction of the total output power sequence, only one prediction method is provided in the embodiment of the present application. There are many existing prediction methods, and the implementer may also use other prediction methods to predict the total output power sequence. This application does not make any specific restrictions.

[0068] Then, the total output power prediction results are analyzed to obtain the suppression factor of the expected time allocation weight of each charging pile at each moment. The expression is:

[0069]

[0070] Wherein, U represents the suppression factor of all charging piles at the current moment; μ represents the average value of the difference between the total output power predicted value at the next a moments and the total output power of the distribution cabinet at the current moment; δ represents the variance of the total output power predicted value at the next a moments; norm() is the normalization function. In the embodiment of the present application, Among them, exp() is an exponential function with a natural constant as the base; μ×δ adopts the same The same method is used for normalization. In other embodiments of the present application, the implementer may also use other normalization methods for normalization.

[0071] μ reflects the trend of the total output power prediction result. When the trend is positive, it means that the total output power is increasing. The smaller the variance of the total output power prediction result, the more reliable the total output power trend is. On the contrary, it means that the total output power change is decreasing. The total output power change in the prediction result is large, so it should be suppressed.

[0072] Step S4, based on the total output power of the distribution cabinet at the current moment, the priority weight, the tram demand characterization factor, the inhibition factor and the time expected allocation weight, determine the allocated power of each charging pile at the current moment; if the current moment is the preset adjustment moment, the output power of each charging pile is allocated according to the allocated power.

[0073] Calculate the dynamic allocation weight of each charging pile at the current moment. The expression is:

[0074] Mb i =b+Rc i +Hg i +U×Q i

[0075] Among them, Mb i represents the final allocation weight of the i-th charging pile at the current moment; b represents the preset initial allocation weight of any charging pile; Rc i Hg is the normalized value of the priority weight of the i-th charging pile at the current moment; i represents the normalized value of the electric vehicle demand characterization factor of the i-th charging pile at the current moment; U represents the inhibition factor of all charging piles at the current moment; Q i Represents the normalized value of the time expected allocation weight of the i-th charging pile at the current moment.

[0076] Use the above method to analyze each charging pile at the current moment, obtain the final allocation weight of each charging pile, and normalize it as follows: Where, Mb i ′ is the normalized value of the allocation weight of the i-th charging pile at the current moment, Mb i 、Mb j are the allocation weights of the i-th and j-th charging piles at the current moment, and M is the number of charging piles.

[0077] Furthermore, the normalized value of the final allocation weight of each charging pile at the current moment is multiplied by the total output power of the distribution cabinet to obtain the allocated power of each charging pile at the current moment, where the allocated power is less than or equal to its maximum power.

[0078] Using the above method, the charging pile power is reallocated every 10 minutes. During this period, whenever a new tram comes to charge at the charging station, the charging pile power is also reallocated after the new tram is connected to the charging gun.

[0079] The schematic diagram of the process of obtaining the tram demand characterization factor is as follows: Figure 2 shown.

[0080] Based on the same inventive concept as the above method, an embodiment of the present application also provides a new energy charging pile power distribution system for multiple charging guns, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-mentioned new energy charging pile power distribution methods for multiple charging guns.

[0081] In summary, the embodiments of the present application provide a power allocation method for a new energy charging pile with multiple charging guns. Through precise dynamic power allocation, it achieves efficient utilization of the total output power, meets the personalized charging needs of electric vehicles, improves user experience, and optimizes charging station operation and management, providing a more intelligent, efficient, and reliable solution for charging new energy vehicles.

[0082] This application introduces multiple allocation weights, takes into account multiple actual demand aspects of tram charging, performs adaptive power allocation, avoids average distribution problems, improves charging efficiency, and ensures that trams receive appropriate charging services; among them, the time-based priority weight allocation follows the first-come-first-served principle, so that first-arriving users can enjoy higher charging power first, which is in line with users' daily usage habits and reduces waiting time; the tram demand characterization factor is calculated according to the remaining power of the tram, so that trams with low power and urgent need for charging can obtain a certain amount of electricity first, improve charging efficiency, ensure the normal use of new energy vehicles, and reduce the risk of users being unable to travel due to insufficient power; based on the total output power change trend prediction result, an inhibition factor is introduced to respond to the total output power change in advance, enhance the stability of the charging process, and avoid charging interruption or delay due to fluctuations in the total output power of the distribution cabinet or changes in the status of other charging piles; through dynamic allocation, user waiting time is reduced, allowing users to accurately estimate the charging completion time and reasonably arrange their itinerary; predict the total output power change and adjust the allocation weight to enhance charging stability and reduce the risk of interruption or delay.

[0083] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the above descriptions are of specific embodiments of the present application. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0084] The various embodiments in this application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0085] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A new energy charging pile power distribution method for multiple charging guns, characterized in that: The method comprises the following steps: Real-time collection of the total output power of the distribution cabinet at the charging station and the output power allocated to each charging pile by the distribution cabinet, as well as the actual remaining power of each charging electric vehicle connected to each charging pile; At the current moment, the priority weight of each charging pile is set based on the usage time of each charging pile; the vehicle demand characterization factor of each charging pile is calculated based on the actual remaining power of all charging electric vehicles connected to each charging pile; based on the difference in the output power of the charging pile corresponding to the time when each electric vehicle started charging and the current moment, the change in the expected charging time of each electric vehicle is analyzed to determine the expected time allocation weight of each charging pile; The total output power of the distribution cabinets at multiple future moments is predicted based on the total output power of the distribution cabinets at historical moments. The suppression factors of all charging piles at the current moment are calculated based on the difference between the total output power prediction values ​​and the total output power of the distribution cabinets at the current moment, as well as the degree of distribution disorder of the total output power prediction values. The allocated power of each charging pile at the current moment is determined based on the total output power of the distribution cabinet at the current moment, the priority weight, the electric vehicle demand characterization factor, the inhibition factor and the time expected allocation weight; if the current moment is the preset adjustment moment, the output power of each charging pile is allocated according to the allocated power.

2. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The actual remaining power is the product of the remaining percentage power of the charging electric vehicle and the total capacity of the battery of the charging electric vehicle.

3. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The process of obtaining the priority weight is as follows: The priority weights are set to M+1 levels from 0 to M, where M is equal to the number of charging piles. For the charging piles currently in use, the current continuous usage time of each charging pile is obtained, and all the charging piles are arranged from large to small according to the current continuous usage time. The priority weight of the charging pile with the longest current continuous usage time is set to the highest priority weight M, and the priority weight is assigned to each charging pile in descending order of arrangement. The priority weight of the charging piles that are not currently in use is set to 0.

4. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The process of obtaining the tram demand characterization factor is as follows: The average of the normalized values ​​of the actual remaining power of the charging electric vehicles connected to all the charging guns of each charging pile is calculated, and the difference between the natural number 1 and the average is used as the electric vehicle demand characterization factor of each charging pile.

5. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The expression of the time expectation allocation weight is: Where Y represents the expected time allocation weight of the current charging pile at the current moment; n is the number of charging guns included in the current charging pile; Pv v Indicates the charging time of the electric vehicle connected to the vth charging gun of the current charging pile at the current moment; Ms v Tb represents the estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile at the current moment; v Indicates the estimated time required to fully charge the electric vehicle connected to the vth charging gun of the current charging pile when charging begins.

6. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The expression of the inhibitory factor is: Among them, U represents the suppression factor of all charging piles at the current moment; μ represents the average value of the difference between the total output power prediction value of all the future moments and the total output power of the distribution cabinet at the current moment; δ represents the variance of the total output power prediction value of all the future moments; norm() is the normalization function.

7. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: The process of obtaining the allocated power is as follows: Calculate the final allocation weight Mb of the i-th charging pile at the current moment i , Mb i The expression is: Mb i =b+Rc i +Hg i +U×Q i , where b represents the preset initial allocation weight of any charging pile; Rc i Hg is the normalized value of the priority weight of the i-th charging pile at the current moment; i represents the normalized value of the electric vehicle demand characterization factor of the i-th charging pile at the current moment; U represents the inhibition factor of all charging piles at the current moment; Q i represents the normalized value of the expected time allocation weight of the i-th charging pile at the current moment; The allocated power of each charging pile at the current moment is determined based on the final allocation weight and the total output power of the distribution cabinet at the current moment.

8. The power distribution method for a new energy charging pile with multiple charging guns according to claim 7, characterized in that: The allocated power of each charging pile at the current moment is: the product of the normalized value of the final allocation weight of each charging pile at the current moment and the total output power of the distribution cabinet.

9. The power distribution method for a new energy charging pile with multiple charging guns according to claim 1, characterized in that: If the current moment is the preset adjustment moment, the output power of each charging pile is distributed by the power distribution, specifically: After every preset time period, the output power of each charging pile is redistributed by the power distribution method; wherein, when a new electric vehicle is charged at any charging pile, the output power of each charging pile is also redistributed.

10. A new energy charging pile power distribution system for multiple charging guns, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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