Ordered charging control system based on switching charging, ordered charging control method and charging facility configuration method

Abstract

The invention discloses an ordered charging control system and method based on switching charging and a charging facility configuration method, and relates to the field of charging control, and the method comprises the steps: switching charging piles to communicate with electric vehicles, obtaining the charging demand information of the electric vehicles, and according to the charging demand information of each electric vehicle in a control range, determining the charging facility configuration of each electric vehicle; calculating charging demand information of switching charging piles, and communicating with an electric vehicle centralized control center through an information concentrator; the electric vehicle centralized control center communicates with the power distribution network, obtains the predicted load of the power distribution network and the configuration condition of the charging facilities, and establishes an optimization control model with the optimal operation index of the power distribution network as the target according to the predicted load of the power distribution network, the configuration condition of the charging facilities and the charging demand information of each switching charging pile; and the charging starting time of each switching charging pile is calculated, and a charging control instruction is issued to each switching charging pile. According to the invention, ordered charging control of the electric vehicle can be realized, and the queuing time of the vehicle owner is reduced.

Description

Technical Field

[0001] The present application relates to the field of charging control, and in particular to an orderly charging control system based on switching charging, an orderly charging control method, and a charging facility configuration method. Background Art

[0002] In the current research on orderly charging control of electric vehicles, it is assumed that the charging facilities built in the parking lot can correspond to electric vehicles one by one, with the goal of minimizing the impact of electric vehicle charging on the power grid, and orderly charging control is achieved through fixed delay or intelligent delay. However, when electric vehicles are used on a large scale, it may be difficult for the charging facilities in residential areas to reach the same number as electric vehicles, especially in residential areas with crowded parking conditions and no fixed parking spaces. Electric vehicles need to queue up for charging after driving, which makes it difficult to achieve orderly charging control of electric vehicles. Summary of the invention

[0003] The purpose of this application is to provide an orderly charging control system, an orderly charging control method and a charging facility configuration method based on switching charging, which can realize orderly charging control of electric vehicles and reduce the waiting time of car owners.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides an orderly charging control system based on switching charging, comprising: an electric vehicle centralized control center, an information concentrator and a plurality of charging facilities; the charging facilities are switching charging piles;

[0006] The switching charging pile communicates with the electric vehicle to obtain the charging demand information of the electric vehicle, calculates the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range, and communicates with the electric vehicle centralized control center through the information concentrator; the charging demand information of the electric vehicle includes the charging power demand and the next use time of the vehicle; the charging demand information of the switching charging pile includes the charging priority, the latest charging end time, the total charging power demand and the total charging time;

[0007] The electric vehicle centralized control center communicates with the distribution network to obtain the predicted load of the distribution network and the configuration of the charging facilities. According to the predicted load of the distribution network, the configuration of the charging facilities and the charging demand information of each switching charging pile, an optimization control model is established with the goal of optimizing the distribution network operation index, the charging start time of each switching charging pile is calculated, and a charging control instruction is issued to each switching charging pile; the charging control instruction is generated based on the charging start time of each switching charging pile; the configuration of the charging facilities includes the configuration quantity, charging power and service capacity of the switching charging piles;

[0008] The switching charging pile charges all electric vehicles within the control range in sequence according to the charging control instruction.

[0009] Optionally, the optimization control model includes: an objective function and constraints; the objective function is established with the goal of minimizing the load variance of the distribution network; the constraints include a charging start time constraint and a charging power constraint;

[0010] The expression of the objective function is:

[0011] The expression of the charging start time constraint is: real_time ≤t ci ≤t ch_i ;

[0012] The expression of the charging power constraint is:

[0013] Where: min represents the minimum value; LV represents the load variance of the distribution network; T c represents the charging start time vector of the switching charging pile, T c =[t c1 ,t c2 ,...,t ci ,...,t cN ]; t ci represents the charging start time of the i-th switching charging pile; N represents the number of switching charging piles; T represents the calculation time period of one day; Δt represents the calculation step length; P l (t) represents the basic load value at time t; P ev (T c ,t,P c , N) represents the total charging load of electric vehicles at time t; P avg Indicates the average load value of the distribution network; t real_time Indicates system time; t ch_i represents the charging end time of the i-th switching charging pile; p ci (t ci ,t) represents the charging power of the i-th switching charging pile at time t; E ch_i It represents the total charging power demand of all electric vehicles within the control range of the i-th switching charging pile.

[0014] Optionally:

[0015] The calculation formula of the charging priority is:

[0016] The calculation formula for the latest charging end time is:

[0017] The calculation formula for the total charging power requirement is:

[0018] The calculation formula for the total charging time is:

[0019] Where: P pr_i represents the charging priority vector of electric vehicles connected to the switching charging pile; sort[] represents the sorting, the later the next use time, the lower the charging priority; t i_ej N represents the next time when the jth electric vehicle in the switching charging pile is used; i represents the number of electric vehicles within the control range of the i-th switching charging pile; t ch_i represents the charging end time of the i-th switching charging pile; max[] represents the maximum value; E ch_i represents the total charging power demand of all electric vehicles within the control range of the i-th switching charging pile; S ij represents the charging target SOC of the jth electric vehicle in the i-th switching charging pile; SoC ij (t i_sj ) represents the starting SOC of the jth electric vehicle in the i-th switching charging pile; t i_sj represents the charging start time of the jth electric vehicle in the i-th switching charging pile; C ij represents the battery capacity of the jth electric vehicle in the i-th switching charging pile; t len_i represents the charging time of the i-th switching charging pile; p ci represents the charging power of the i-th switching charging pile; Δt ij Indicates the switching operation time of the charging facility.

[0020] Optionally, a Monte Carlo simulation is used to obtain the charging start SOC, charging start time and next use time of the electric vehicle; the total charging load of the electric vehicle is equal to the superposition of the charging power of each switching charging pile at each time.

[0021] Optionally, the switching charging pile includes a DC charging pile and an AC charging pile;

[0022] When the switching charging pile is an AC charging pile, the charging demand information of the electric vehicle also includes the charging power of the on-board charger;

[0023] When the switching charging pile is a DC charging pile, the charging demand information of the switching charging pile also includes the charging power of the DC charging pile.

[0024] Optionally, a particle swarm optimization algorithm is used to solve the optimization control model to obtain the charging start time of each switching charging pile.

[0025] In a second aspect, the present application provides an orderly charging control method based on switching charging, which is applied to the orderly charging control system based on switching charging, comprising:

[0026] Obtain information on electric vehicle charging demand, distribution network forecast load, and charging facility configuration;

[0027] Calculate the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range;

[0028] According to the predicted load of the distribution network, the configuration of charging facilities and the charging demand information of each switching charging pile, an optimization control model is established with the goal of optimizing the distribution network operation indicators to calculate the charging start time of each switching charging pile;

[0029] A charging control instruction is generated based on the charging start time of each switching charging pile to control the switching charging pile to charge all electric vehicles within the control range in sequence.

[0030] In a third aspect, the present application provides a charging facility configuration method based on switching charging, which is applied to the orderly charging control system based on switching charging, including:

[0031] An iterative simulation method is used to determine the configuration of charging facilities based on the number of electric vehicles in the target area, the driving patterns of electric vehicles and the proportion of electric vehicle types.

[0032] Optionally, when the charging pile is switched to an AC charging pile, an iterative simulation method is used to determine the configuration of the charging facilities according to the number of electric vehicles in the target area, the driving pattern of electric vehicles, and the composition ratio of electric vehicle types, including:

[0033] Obtain the number of electric vehicles in the target area, the driving patterns of electric vehicles, and the composition ratio of electric vehicle types, and set the number of Monte Carlo simulations;

[0034] Set the initial value of the configuration number of switching charging piles to 1 and the initial value of the number of iterations to 1;

[0035] Monte Carlo simulation is used to obtain the driving pattern data of all electric vehicles in the target area, and the corresponding vehicle model parameters are randomly matched according to the composition ratio of electric vehicle types; the vehicle model parameters include battery capacity, cruising range and charging power of the on-board charger;

[0036] The charging power of the on-board charger is determined as the charging power of the switching charging pile. According to the driving law data and vehicle model parameters of all electric vehicles in the target area and the configuration number of the switching charging piles, orderly charging control is simulated, and the charging power satisfaction rate of electric vehicles and the load variance index of the distribution network are calculated;

[0037] If the current value of the number of iterations is less than the number of Monte Carlo simulations, increase the number of iterations by 1 and return to step "using Monte Carlo simulation to obtain the driving law data of all electric vehicles in the target area, and randomly match the corresponding vehicle model parameters according to the composition ratio of electric vehicle types" until the number of Monte Carlo simulations is reached;

[0038] If the current value of the number of configurations of the switching charging piles is less than the number of electric vehicles in the target area, the number of configurations of the switching charging piles is increased by 1, and the process returns to the step of "using Monte Carlo simulation to obtain the driving law data of all electric vehicles in the target area, and randomly matching the corresponding vehicle model parameters according to the composition ratio of electric vehicle types" until the number of electric vehicles in the target area is reached;

[0039] According to the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network obtained in each simulation, the optimal configuration quantity and service capacity of the switching charging piles are determined.

[0040] Optionally, when the switching charging pile is a DC charging pile, the configuration quantity of the switching charging pile satisfies the configuration quantity constraint, and the charging power of the switching charging pile satisfies the charging power constraint;

[0041] The expression of the configuration quantity constraint is: N min ≤N≤N max ;

[0042] The expression of the charging power constraint is: 0<p c ≤P c,max ;

[0043] Where N represents the number of configurations of the switching charging piles; N min N represents the minimum number of charging facilities required to meet the charging demand of electric vehicles, which is a function of the charging power of the switching charging pile; max Indicates the maximum number of charging facilities; p c Indicates the charging power of the switching charging pile; P c,max Indicates the maximum charging power that an electric vehicle can withstand.

[0044] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0045] The present application provides an orderly charging control system based on switching charging, an orderly charging control method and a charging facility configuration method, the orderly charging control system includes: an electric vehicle centralized control center, an information concentrator and several charging facilities; the charging facilities are switching charging piles. Among them, the switching charging pile communicates with the electric vehicle to obtain the charging demand information of the electric vehicle, calculates the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range, and communicates with the electric vehicle centralized control center through the information concentrator; the electric vehicle centralized control center communicates with the distribution network to obtain the predicted load of the distribution network and the configuration of the charging facilities, and establishes an optimization control model with the goal of optimizing the distribution network operation index according to the predicted load of the distribution network, the configuration of the charging facilities and the charging demand information of each switching charging pile, calculates the charging start time of each switching charging pile, and issues charging control instructions to each switching charging pile to control the switching charging pile to charge all electric vehicles within the control range in turn, thereby realizing the orderly charging control of the electric vehicle, thereby reducing the waiting time of the car owner. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments will be briefly introduced below. 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 paying creative work.

[0047] Figure 1 A schematic diagram of the structure of an orderly charging control system based on switching charging provided in this application;

[0048] Figure 2 A schematic diagram of the working process of the orderly charging control system based on switching charging provided in this application;

[0049] Figure 3 A real-time calculation flow chart of an orderly charging control system based on switching charging provided in this application;

[0050] Figure 4 The power demand curves under two different calculation steps provided for this application;

[0051] Figure 5 Load curve diagrams for several different charging facility configurations provided for this application;

[0052] Figure 6 A curve chart showing the relationship between the number of charging facilities, energy satisfaction rate, and load variance provided for this application. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0054] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0055] When there are few charging facilities in residential areas, electric vehicles need to queue up for charging after driving. At this time, if orderly charging control is to be carried out, manual switching is required at the beginning and end of charging for each vehicle, which is not conducive to the implementation of orderly charging, especially at night. In view of these problems, an orderly charging control system and method based on switching charging is proposed, which can be achieved by switching charging piles (machines) of "one machine with multiple chargers".

[0056] Exemplarily, the present application provides an orderly charging control system based on switching charging, such as Figure 1 As shown, the system includes: an electric vehicle centralized control center, an information concentrator and several charging facilities; the charging facilities are switching charging piles. The switching charging piles can serve multiple electric vehicles, but only charge one electric vehicle at a time. When a certain electric vehicle is charged, it switches to the next one until all electric vehicles are served and charging is completed.

[0057] The switching charging pile communicates with the electric vehicle to obtain the charging demand information of the electric vehicle, calculates the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range, and communicates with the electric vehicle centralized control center through the information concentrator. The charging demand information of the electric vehicle includes the charging power demand and the next use time of the vehicle; the charging demand information of the switching charging pile includes the charging priority, the latest charging end time, the total charging power demand and the total charging time. The electric vehicle centralized control center communicates with the distribution network to obtain the distribution network predicted load and the charging facility configuration, and establishes an optimization control model with the distribution network operation index as the goal according to the distribution network predicted load, the charging facility configuration and the charging demand information of each switching charging pile, calculates the charging start time of each switching charging pile, and issues a charging control instruction to each switching charging pile. The charging control instruction is generated based on the charging start time of each switching charging pile; the charging facility configuration includes the configuration quantity, charging power and service capacity of the switching charging pile. The switching charging pile charges all electric vehicles within the control range in turn according to the charging control instruction.

[0058] Correspondingly, the present application provides an orderly charging control method based on switching charging, which is applied to the above-mentioned orderly charging control system based on switching charging, including: obtaining the charging demand information of electric vehicles, the predicted load of the distribution network and the configuration of charging facilities; calculating the charging demand information of the switching charging piles according to the charging demand information of each electric vehicle within the control range; establishing an optimization control model with the goal of optimizing the distribution network operation indicators according to the predicted load of the distribution network, the configuration of charging facilities and the charging demand information of each switching charging pile, and calculating the charging start time of each switching charging pile; generating charging control instructions based on the charging start time of each switching charging pile to control the switching charging pile to charge all electric vehicles within the control range in turn.

[0059] Wherein, the switching charging pile includes a DC charging pile and an AC charging pile. When the switching charging pile is an AC charging pile, the charging demand information of the electric vehicle also includes the charging power of the on-board charger. When the switching charging pile is a DC charging pile, the charging demand information of the switching charging pile also includes the charging power of the DC charging pile.

[0060] According to Figure 1 In the control system structure shown, after the electric vehicle has finished driving, it parks in a parking space and communicates with the switching charging pile to exchange information on charging power demand, charging power and next driving time; each switching charging pile calculates the total charging power demand, the latest charging end time and the charging priority order based on the charging demand information of the electric vehicles within the control range, and communicates with the electric vehicle centralized control center through the information concentrator; the centralized control center establishes an optimization control model based on the predicted load of the distribution network and the charging demand information of each switching charging pile, with the goal of optimizing the distribution network operation indicators, and calculates the charging start time of each switching charging pile. Since the time when the electric vehicle connects to the switching charging pile is uncertain, in order to achieve real-time and orderly control, the electric vehicle centralized control center updates the orderly charging control command according to a certain period based on the real-time information uploaded by each switching charging pile, and reports the real-time power consumption plan to the power grid dispatching center. Figure 2 Shown is a schematic diagram of the working process of an orderly charging control system based on switching charging.

[0061] As mentioned above, electric vehicle charging facilities, namely switching charging piles, are divided into two types: AC charging piles and DC charging piles. The AC charging pile is equivalent to a switch, which performs AC / DC conversion of electric energy through the on-board charger, which is generally slow charging, and the charging power is determined by the on-board charger; the DC charging pile can directly complete the AC / DC conversion function and charge through the DC charging port of the electric vehicle, which is generally fast charging. For different types of switching charging piles, the above switching charging control method is slightly different: for AC charging piles, electric vehicles need to interact with the charging control system to determine the charging power demand, the next driving time, and the charging power of the on-board charger; for DC chargers, there is no need to interact with the charging power of the on-board charger. The orderly charging control model (i.e., the optimization control model) and the charging facility configuration method under the two charging facilities are described below.

[0062] The goal of orderly charging is to optimize the operation of the distribution network while meeting the charging needs of users. Figure 1 The orderly charging system structure shown in the figure, when performing orderly charging control, must first determine the number of switching charging piles in the residential area, the number of electric vehicles served by each switching charging pile (i.e., service capacity) and the charging power of the switching charging piles, and on this basis optimize the charging start time of each switching charging pile, so the following optimization control model can be established.

[0063] (1) Objective function.

[0064] The electric vehicle charging load based on switching charging pile access is a centralized access load. Here, an orderly charging control model is established with the minimum distribution network load variance as the objective function (ignoring network losses), as shown in Equations (1) and (2).

[0065]

[0066] Where: min represents the minimum value; LV represents the load variance of the distribution network; T c represents the charging start time vector of the switching charging pile, T c =[t c1 ,t c2 ,...,t ci ,...,t cN ]; t ci Indicates the charging start time of the i-th switching charging pile; N indicates the number of switching charging piles; T indicates the calculation time period of one day, which is determined by the calculation step length. For example, when the calculation step length is 0.1h, T=240; P c represents the charging power vector of the switching charging pile, P c =[p c1 ,p c2 ,...p ci ,....pcN ]; P l (t) represents the basic load value at time t; P ev (T c ,t,P c , N) represents the total charging load of electric vehicles at time t; P avg Indicates the average load value of the distribution network.

[0067] (2)Constraints.

[0068] When the configuration quantity, service capacity and charging power of the switching charging pile are determined, the charging start time constraint and charging power constraint of the i-th switching charging pile are shown in equations (3) and (4).

[0069] t real_time ≤t ci ≤t ch_i (3)

[0070]

[0071] Where: t real_time Indicates system time; t ch_i represents the charging end time of the i-th switching charging pile; p ci (t ci ,t) represents the charging power of the i-th switching charging pile at time t. If it is a DC charging pile, the charging power is the charging power of the DC charging pile. If it is an AC charging pile, the charging power is the charging power of the on-board charger. E ch_i It represents the total charging power demand of all electric vehicles within the control range of the i-th switching charging pile.

[0072] When an electric vehicle is connected to a switching charging pile, it exchanges the state of charge (SOC), battery capacity, charging target, charging power and next time of use of the vehicle with the switching charging pile. The switching charging pile controller sorts the charging priority according to the next time of use of the electric vehicle, calculates the charging end time, charging power requirement, total charging time, etc. of the switching charging pile, and uploads this information to the electric vehicle centralized control center. For the i-th switching charging pile, the above information is calculated using equations (5) to (8) respectively.

[0073]

[0074] Where: P pr_i represents the charging priority vector of electric vehicles connected to the switching charging pile; sort[] represents the sorting, the later the next use time, the lower the charging priority; t i_ej N represents the next time when the jth electric vehicle in the switching charging pile is used; irepresents the number of electric vehicles within the control range of the i-th switching charging pile; t ch_i represents the charging end time of the i-th switching charging pile; max[] represents the maximum value; t i_sj represents the charging start time of the jth electric vehicle in the i-th switching charging pile; t len_i represents the charging time of the i-th switching charging pile; S ij represents the charging target SOC of the jth electric vehicle in the i-th switching charging pile; C ij represents the battery capacity of the jth electric vehicle in the i-th switching charging pile; SoC ij (t i_sj ) represents the charging starting SOC of the jth electric vehicle in the i-th switching charging pile; p ci represents the charging power of the i-th switching charging pile; Δt ij Indicates the charging facility switching operation time. In this application, the charging target SOC is set to 1.

[0075] Assuming that the use of electric vehicles does not change the user's driving pattern, the starting SOC of electric vehicle charging, the end time of driving, and the start time of the next driving are realized through the Monte Carlo simulation method. Therefore, the charging load based on switching charging can be carried out according to the following steps:

[0076] Step 1: Generate a random number sequence with coupling characteristics, including charging start time, next driving start time, daily driving mileage, etc.

[0077] Step 2: Simulate electric vehicle driving. The change of the power battery SOC of the jth electric vehicle before and after driving in the i-th switching charging pile is calculated according to formula (9).

[0078] SoC ij (t i_sj )=SoC ij (t i_ej )-d ij / D ij (9)

[0079] Where: d ij and D ij They represent the daily mileage and maximum cruising range of electric vehicles respectively.

[0080] Step 3: Simulate electric vehicle charging. The change of SOC during electric vehicle charging can be calculated according to formula (10), and the charging power of the i-th switching charging pile at each moment is shown in formula (11).

[0081] SoC ij (t i_ej )=SoC ij (t i_sj)+p ci ·t ch_ij / C ij (10)

[0082]

[0083] Where: t ch_ij Indicates the charging completion time of the j-th electric vehicle in the i-th switching charging pile.

[0084] When the number of electric vehicle switching charging piles, charging power and charging time are determined, the total charging load is equal to the superposition of the charging power of each switching charging pile at each time, as shown in expression (12).

[0085]

[0086] Where: P ev (t) represents the total charging power of electric vehicles; N represents the number of switching charging piles.

[0087] The particle swarm optimization algorithm (PSO) is used to solve the above orderly charging control problem. The charging start time of each switching charging pile is used as the particle position, so a particle swarm of size m can be established, as shown in expression (13).

[0088]

[0089] Where: T pso represents the charging start time particle group; x ab Indicates the charging start time of the bth switching charging pile in the ath particle.

[0090] The objective function of the control model is used as the fitness function of the particle swarm algorithm. In the iterative calculation process, the charging time of each switching charging pile is determined according to formula (13) and the system time, and the load curve after charging load adjustment is calculated according to formula (12). Then, the fitness value of the PSO algorithm is obtained according to formula (1); then the iterative method of the PSO algorithm can be used to find the optimal charging start time.

[0091] Summarizing the above control models and calculation methods, we can get Figure 3 The real-time calculation process of the switching orderly charging control system is shown, where the left half describes the control process of the electric vehicle centralized control center, and the right half is the control process of switching charging piles.

[0092] Furthermore, the present application also provides a charging facility configuration method based on switching charging, which is applied to the above-mentioned orderly charging control system based on switching charging, including: using an iterative simulation method to determine the charging facility configuration according to the number of electric vehicles in the target area, the driving patterns of electric vehicles and the composition ratio of electric vehicle types.

[0093] The configuration of AC charging facilities only requires determining the configuration quantity and service capacity of the charging facilities, while the configuration of DC charging facilities requires determining the configuration quantity, charging power and service capacity of the charging facilities. Therefore, the configuration methods of the two types of charging facilities are slightly different. In addition, considering the driving patterns of electric vehicles and the randomness of charging demand, the iterative simulation method is used here for calculation.

[0094] (1) Configuration method of AC charging facilities.

[0095] The number of AC charging facilities is mainly determined by the driving patterns of electric vehicle users, the charging power of the on-board charger, and the power consumption characteristics of electric vehicles. The driving patterns of electric vehicles are highly random, and the on-board chargers and power consumption characteristics of different electric vehicles are somewhat different. These factors need to be fully considered when configuring charging facilities. Therefore, the following configuration method is proposed:

[0096] Step 1: Determine the number of electric vehicles in the target area (set as N ev ), the driving law of electric vehicles (here the driving law of fuel vehicles is used as a substitute), the composition ratio of electric vehicle types and the charging power of the on-board charger, and the number of Monte Carlo simulations N sim .

[0097] Step 2: Set the number of charging facilities (switching charging piles) N=1.

[0098] Step 3: Use Monte Carlo simulation technique to get N ev The driving pattern data of each electric vehicle (driving start / end time, daily mileage) is collected and randomly matched with corresponding vehicle model parameters, including battery capacity, cruising range and charging power of the on-board charger.

[0099] Step 4: Use the above orderly charging control model to simulate orderly charging control, and calculate the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network.

[0100] In step 4, by simulating orderly charging control, we can obtain the charging power change curve in different time periods, average charging power, charging time, charging time distribution in different time periods, grid load curve, charging cost, grid expansion cost savings, battery life impact, battery status parameters, such as battery SOC change curve and other data.

[0101] Step 5: Return to step 3 and simulate N repeatedly sim Second-rate.

[0102] Step 6: If N <N ev , the number of charging facilities is updated to N=N+1, and the iteration is returned to step 3, otherwise the iteration is terminated.

[0103] Step 7: Based on the charging capacity satisfaction rate and the load variance index of the distribution network obtained in each simulation, analyze the optimal number of charging facilities to be configured and determine the service capacity of each switching charging pile.

[0104] In step 7, the charging capacity satisfaction rate = (E final -E init ) / E desired x100%. Among them, E init (Unit: kWh) is the remaining battery capacity before charging, E final is the battery capacity after charging, E desired The charging capacity expected by the user. in, is the average load, P(t) is the load value of the distribution network at different times, t is the time number, and T is the calculation time period.

[0105] Through simulation, the charging power satisfaction rate and the load variance index data of the distribution network under different numbers of charging facilities are obtained. The number of charging facilities under different factors, the corresponding charging power satisfaction rate value and the distribution network load value are recorded. Observe the changing trend of the charging power satisfaction rate as the number of charging facilities increases. If the charging power satisfaction rate increases rapidly with the increase in the number of charging facilities, it means that the current number of charging facilities may be insufficient; if the increase in the charging power satisfaction rate gradually slows down or even tends to stabilize, it means that it may be close to or reach a more reasonable range of charging facilities. Also observe the changes in the distribution network load index under different numbers of charging facilities. If the distribution network load rises sharply with the increase in the number of charging facilities, it may affect the stability and safety of the distribution network, which indicates that the number of charging facilities may be too many. Considering the charging power satisfaction rate and the distribution network load index comprehensively, find a balance point so that the charging power satisfaction rate is high and the distribution network load is within an acceptable range. The number of charging facilities near this balance point is the optimal configuration number. Once the optimal configuration number is determined, the service capacity of each switching charging pile is calculated based on the total charging demand and the number of charging facilities.

[0106] (2) Configuration method of DC charging facilities.

[0107] In order to ensure the charging power demand of electric vehicles, a sufficient number of charging facilities must be built. However, the number of charging facilities is affected by the charging power. These two variables jointly determine the service capacity of the charging facilities. For residential communities with a limited number of charging facilities, the service capacity of the charging facilities can be improved by increasing the charging power. Therefore, the following configuration quantity constraints and charging power constraints are implemented.

[0108] N min ≤N≤N max (14)

[0109] 0<p c ≤P c,max (15)

[0110] In formula (14), N represents the number of configurations of switching charging piles; min N represents the minimum number of charging facilities required to meet the charging demand of electric vehicles, which is a function of the charging power of the switching charging pile; max represents the maximum number of charging facilities; in formula (15), p c Indicates the charging power of the switching charging pile; P c,max Indicates the maximum charging power that an electric vehicle can withstand.

[0111] The configuration of charging facilities mainly includes two parameters: the number of charging facilities and the rated charging power. These two parameters affect each other. Therefore, when configuring charging facilities, you need to determine one parameter first. The specific configuration method is described as follows.

[0112] If the rated power of the charging facility is given, the calculation steps for the number of charging facilities are as follows:

[0113] Step 1: Determine the number of electric vehicles in the area to be studied (set as N ev ), the driving law of electric vehicles (replaced by the driving law of fuel vehicles), and the composition ratio of electric vehicle types, setting the number of Monte Carlo simulations N sim , set the rated charging power of the charging facility to p c .

[0114] Step 2: Set the number of charging facilities N = 1.

[0115] Step 3: Use Monte Carlo simulation technique to get N ev The driving pattern data of electric vehicles is collected and randomly matched with corresponding vehicle model parameters, including battery capacity and range.

[0116] Step 4: Use the above orderly charging control model to simulate orderly charging control, and calculate the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network.

[0117] Step 5: Return to step 3 and simulate N repeatedly sim Second-rate.

[0118] Step 6: If N <N ev , the number of charging facilities is updated to N=N+1, and the iteration is returned to step 3, otherwise the iteration is terminated.

[0119] Step 7: Analyze the optimal number of charging facilities based on the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network obtained in each simulation.

[0120] If the number of charging facilities is given, the calculation method of the charging facility power configuration is similar to the above, and the iterative calculation steps are as follows:

[0121] Step 1: Determine the number of electric vehicles N in the area to be studied ev , the driving habits of electric vehicles, and the composition ratio of electric vehicle types, setting the number of Monte Carlo simulations N sim , set the number N of charging facilities to be configured.

[0122] Step 2: Set the charging power p of the charging facility c =0.1.

[0123] Step 3: Use Monte Carlo simulation technique to get N ev The driving pattern data of electric vehicles is collected and randomly matched with corresponding vehicle model parameters, including battery capacity and range.

[0124] Step 4: Simulate orderly charging control and calculate the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network.

[0125] Step 5: Return to step 3 and simulate N repeatedly sim Second-rate.

[0126] Step 6: If p c <P c,max , charging power update p c =p c +0.1 and return to step 3, otherwise end the iteration.

[0127] Step 7: Analyze the optimal charging power of the charging facilities based on the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network obtained in each simulation.

[0128] For a given number of charging facilities, multiple simulations are performed, each with a different charging power, and the charging power satisfaction rate of electric vehicles and the load variance index of the distribution network obtained from each simulation are recorded. Observe the change of the charging power satisfaction rate with the charging power. Generally speaking, as the charging power increases and the charging speed increases, the charging power satisfaction rate may increase. However, when the charging power increases to a certain extent, it may be limited by factors such as battery characteristics, and the charging power satisfaction rate may not increase significantly or may even decrease. At the same time, pay attention to the change of the distribution network load index with the charging power. The increase in charging power will cause the load of the distribution network to increase. If the load exceeds the carrying capacity of the distribution network, it will affect the stability of the power grid. Considering the charging power satisfaction rate and the distribution network load index comprehensively, find a charging power value that makes the charging power satisfaction rate high and the distribution network load within the tolerable range. This power value is the optimal charging power. By drawing the curve of the charging power satisfaction rate and the distribution network load index changing with the charging power, the range of the optimal charging power can be intuitively determined, and then the specific value can be determined through further analysis and debugging.

[0129] Since the number of charging facilities and charging power affect each other, the combination of the number of charging facilities and charging power used to switch orderly charging control is not unique. The above two calculation steps can be combined and all combinations can be obtained through iteration. The calculation steps are as follows:

[0130] Step 1: Determine the number of electric vehicles N in the community to be studied ev , the driving rules of electric vehicles, and the composition ratio of electric vehicle types, setting the number of Monte Carlo simulations N sim , set the number of charging facilities to be configured N=1.

[0131] Step 2: Set the charging power p of the charging facility c =0.1.

[0132] Step 3: Use Monte Carlo simulation technique to get N ev The driving pattern data of electric vehicles is collected and randomly matched with corresponding vehicle model parameters, including battery capacity and range.

[0133] Step 4: Simulate orderly charging control and calculate the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network.

[0134] Step 5: Return to step 3 and simulate N repeatedly sim Second-rate.

[0135] Step 6: If p c <P c,max , charging power update p c =p c +0.1 and return to step 3 iteration, otherwise go to step 7.

[0136] Step 7: Analyze the optimal charging power of the charging facilities based on the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network obtained in each simulation.

[0137] Step 8: Update the number of charging facilities N = N + 1. If N <N ev , return to step 2, otherwise the iterative calculation ends.

[0138] Step 9: Based on the above calculation, the optimal charging power corresponding to different numbers of charging facilities is obtained, and then the optimal number of charging facilities and charging power are selected according to the actual situation to determine the service capacity of each charger.

[0139] The configuration process of the above electric vehicle charging facilities is a process of continuous iteration and update, which requires a long calculation cycle. In order to reduce the number of update calculations, at different charging powers, the minimum number of charging facilities can be calculated first, that is, the minimum number of charging facilities required to meet the charging needs of electric vehicles. Iterative calculation is performed through the following steps:

[0140] Step 1: Set the initial value of the number of charging facilities to N = 1 and the power of the charging facilities to p c , the number of electric vehicles is N ev .

[0141] Step 2: Use Monte Carlo simulation technology to obtain N ev The driving pattern data of electric vehicles is collected and randomly matched with corresponding vehicle model parameters, including battery capacity and range.

[0142] Step 3: Set the charging start time of the electric vehicle that finishes driving earliest as the iteration start time t, the calculation step length as △t, and set the number of electric vehicles that have completed charging n ev =0.

[0143] Step 4: Electric vehicles are charged immediately after the driving is completed. When the number of electric vehicles that need to be charged is greater than the number of charging facilities, the electric vehicles queue up and wait for charging according to the driving completion time.

[0144] Step 5: Update time t=t+△t.

[0145] Step 6: The charging electric vehicle updates the SOC state according to formula (10) and determines whether there is an electric vehicle that has finished charging. If not, return to step 5; if yes, n ev =n ev +1, when n ev <N ev When n ev =N ev, go to step 7.

[0146] Step 7: Determine whether the end time of electric vehicle charging exceeds the charging time limit. If so, update the number of charging facilities to N=N+1 and return to step 2. If not, the iteration ends and the minimum number of charging facilities is N, which is N. min .

[0147] By changing the power of the charging facilities, the minimum number of charging facilities under different charging powers can be calculated. min When the charging facilities can only meet the user's charging power demand, the charging load cannot be adjusted. Therefore, the necessary condition for using DC charging piles to achieve switching orderly charging is that the number of charging facilities is greater than N. min .

[0148] The following is a specific example of AC charging facility configuration.

[0149] 1. Example parameter setting

[0150] (1) Electric vehicle charging demand parameters.

[0151] In order to verify the effectiveness of the above-mentioned switching orderly charging control system, as well as the relationship between the charging facility configuration and the charging power, the charging demand of electric vehicles and traditional loads in a certain place are taken as an example for verification; the charging demand of electric vehicles is calculated based on the driving rules of fuel vehicles.

[0152] (2) Algorithm parameter setting.

[0153] When using the PSO algorithm, the population size is set to 50, the maximum number of iterations is set to 150, the maximum value of the particle velocity is set to 5, and the minimum value is set to -5.

[0154] (3) Determine the iterative calculation step size.

[0155] The iterative calculation step size is related to the accuracy of the simulation calculation. The smaller the simulation step size, the higher the calculation accuracy, but the longer the calculation time. Figure 4The figure shows the comparison curves of the actual charging power and the total power demand of electric vehicles when AC charging piles are used to switch to orderly charging under different numbers of charging facilities when the calculation step length is 0.1h (T=240) and 0.01h (T=2400). The number of electric vehicles is 500. Before the intersection, the actual charging power is less than the required power because the number of charging facilities cannot meet the charging power demand; with the increase in the number of charging facilities, the calculation error of the actual charging power increases, because each charging facility has a certain calculation error. When the number of charging facilities increases, the cumulative charging power error will increase; comparing the two curves with a step length of 0.1h and a step length of 0.01h, it can be seen that the smaller the calculation step length, the smaller the increase in the cumulative charging power error. When the calculation step length is 0.01h, the actual charging power is basically consistent with the total power demand. Therefore, the step length is set to 0.01h in the orderly charging calculation.

[0156] 2. Simulation calculation of AC charging facility configuration.

[0157] In order to verify that the above-mentioned switching orderly charging control system can achieve orderly charging under the premise of meeting the charging needs of users, it is first assumed that the number of electric vehicle AC charging facilities is 100, 200, 300 and 500 respectively, and orderly charging control is performed according to the above-mentioned orderly charging model, and the following is obtained: Figure 5 The charging load curve after orderly charging control is shown in the figure. It can be seen from the figure that: under the four charging facility configuration numbers, the charging load of electric vehicles is transferred to the nighttime load trough period; when the number of charging facilities is 100, due to the long working time of each charger and the early charging start time of each charger, the charging load will significantly increase the evening peak value of the original load, while when the number of charging facilities is 200 and 300, the charging load has little impact on the evening peak.

[0158] Table 1 shows the user charging energy satisfaction rate (ESR) and distribution network load variance (LV) data. It can be seen from the table that when the number of AC charging facilities is 300 and 500, the load variance index of the distribution network can be optimized while meeting the user's charging needs; when the number of charging facilities is 200, the energy satisfaction degree reaches 98.7%, which is close to full satisfaction.

[0159] Table 1 Distribution network load variance and charging power satisfaction rate under different charging facility configuration numbers

[0160] Number of charging facilities 500 300 200 100 LV 0.20 0.20 0.25 0.33 ESR 100％ 100％ 98.7％ 93.4％

[0161] In order to analyze the control effect of switching charging system under more charging facility configurations and obtain the optimal charging facility configuration number, the number of charging facilities is set to change from 1 to 500, and the user charging power satisfaction rate and distribution network load variance under different charging facility configuration numbers are calculated, and the following is obtained: Figure 6 The curve shown. It can be seen from the figure that: as the number of charging facilities increases, the user charging power satisfaction rate increases, and the distribution network load variance becomes smaller and smaller; the charging power demand satisfaction rate reaches the optimal value earlier than the load variance, so there is an optimal number of charging facilities that can meet the user's charging needs and make the load variance after switching charging reach the optimal value; it can be seen from the figure that when the number of charging facilities reaches about 248, the power satisfaction rate and load variance can both reach the optimal value, so this value is the optimal configuration number. At this time, the service capacity of 244 AC charging piles is 2, and the service capacity of 4 AC charging piles is 3.

[0162] The following conclusions can be drawn from the above simulation calculations:

[0163] 1) AC charging facilities can be configured to switch charging modes to achieve orderly charging control of electric vehicles.

[0164] 2) There is an optimal configuration quantity that can optimize the distribution network load variance while satisfying the user charging power satisfaction rate.

[0165] 3) When using AC charging facilities to achieve switching orderly charging control, the service capacity of each charger is limited to only 2 or 3 electric vehicles. Therefore, DC charging facilities can be considered to achieve switching control.

[0166] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0167] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An orderly charging control system based on switching charging, characterized in that: include: Electric vehicle centralized control center, information concentrator and several charging facilities; The charging facility is a switching charging pile; The switching charging pile communicates with the electric vehicle to obtain the charging demand information of the electric vehicle, calculates the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range, and communicates with the electric vehicle centralized control center through the information concentrator; the charging demand information of the electric vehicle includes the charging power demand and the next use time of the vehicle; the charging demand information of the switching charging pile includes the charging priority, the latest charging end time, the total charging power demand and the total charging time; The electric vehicle centralized control center communicates with the distribution network to obtain the predicted load of the distribution network and the configuration of the charging facilities. According to the predicted load of the distribution network, the configuration of the charging facilities and the charging demand information of each switching charging pile, an optimization control model is established with the goal of optimizing the distribution network operation index, the charging start time of each switching charging pile is calculated, and a charging control instruction is issued to each switching charging pile; the charging control instruction is generated based on the charging start time of each switching charging pile; the configuration of the charging facilities includes the configuration quantity, charging power and service capacity of the switching charging piles; The switching charging pile charges all electric vehicles within the control range in sequence according to the charging control instruction.

2. The orderly charging control system based on switching charging according to claim 1 is characterized in that: The optimization control model includes: an objective function and constraints; the objective function is established with the goal of minimizing the load variance of the distribution network; the constraints include a charging start time constraint and a charging power constraint; The expression of the objective function is: The expression of the charging start time constraint is: real_time ≤t ci ≤t ch_i ; The expression of the charging power constraint is: Where: min represents the minimum value; LV represents the load variance of the distribution network; T c represents the charging start time vector of the switching charging pile, T c =[t c1 ,t c2 ,...,t ci ,...,t cN ]; t ci represents the charging start time of the i-th switching charging pile; N represents the number of switching charging piles; T represents the calculation time period of one day; Δt represents the calculation step length; P l (t) represents the basic load value at time t; P ev (T c ,t,P c , N) represents the total charging load of electric vehicles at time t; P avg Indicates the average load value of the distribution network; t real_time Indicates system time; t ch_i represents the charging end time of the i-th switching charging pile; p ci (t ci ,t) represents the charging power of the i-th switching charging pile at time t; E ch_i It represents the total charging power demand of all electric vehicles within the control range of the i-th switching charging pile.

3. The orderly charging control system based on switching charging according to claim 1 is characterized in that: The calculation formula of the charging priority is: The calculation formula for the latest charging end time is: The calculation formula for the total charging power requirement is: The calculation formula for the total charging time is: Where: P pr_i represents the charging priority vector of electric vehicles connected to the switching charging pile; sort[] represents the sorting, the later the next use time, the lower the charging priority; t i_ej N represents the next time when the jth electric vehicle in the switching charging pile is used; i represents the number of electric vehicles within the control range of the i-th switching charging pile; t ch_i represents the charging end time of the i-th switching charging pile; max[] represents the maximum value; E ch_i represents the total charging power demand of all electric vehicles within the control range of the i-th switching charging pile; S ij represents the charging target SOC of the jth electric vehicle in the i-th switching charging pile; SoC ij (t i_sj ) represents the starting SOC of the jth electric vehicle in the i-th switching charging pile; t i_sj represents the charging start time of the jth electric vehicle in the i-th switching charging pile; C ij represents the battery capacity of the jth electric vehicle in the i-th switching charging pile; t len_i represents the charging time of the i-th switching charging pile; p ci represents the charging power of the i-th switching charging pile; Δt ij Indicates the switching operation time of the charging facility.

4. The orderly charging control system based on switching charging according to claim 3 is characterized in that: Monte Carlo simulation is used to obtain the charging starting SOC, charging starting time and next use time of the electric vehicle; the total charging load of the electric vehicle is equal to the superposition of the charging power of each switching charging pile at each time.

5. The orderly charging control system based on switching charging according to claim 1, characterized in that: The switching charging pile includes a DC charging pile and an AC charging pile; When the switching charging pile is an AC charging pile, the charging demand information of the electric vehicle also includes the charging power of the on-board charger; When the switching charging pile is a DC charging pile, the charging demand information of the switching charging pile also includes the charging power of the DC charging pile.

6. The orderly charging control system based on switching charging according to claim 1, characterized in that: The particle swarm optimization algorithm is used to solve the optimization control model to obtain the charging start time of each switching charging pile.

7. An orderly charging control method based on switching charging, applied to the orderly charging control system based on switching charging according to any one of claims 1 to 6, characterized in that: include: Obtain information on electric vehicle charging demand, distribution network forecast load, and charging facility configuration; Calculate the charging demand information of the switching charging pile according to the charging demand information of each electric vehicle within the control range; According to the predicted load of the distribution network, the configuration of charging facilities and the charging demand information of each switching charging pile, an optimization control model is established with the goal of optimizing the distribution network operation indicators to calculate the charging start time of each switching charging pile; A charging control instruction is generated based on the charging start time of each switching charging pile to control the switching charging pile to charge all electric vehicles within the control range in sequence.

8. A charging facility configuration method based on switching charging, applied to the orderly charging control system based on switching charging according to any one of claims 1 to 6, characterized in that: include: An iterative simulation method is used to determine the configuration of charging facilities based on the number of electric vehicles in the target area, the driving patterns of electric vehicles and the proportion of electric vehicle types.

9. The charging facility configuration method based on switching charging according to claim 8, characterized in that: When the charging pile is switched to an AC charging pile, an iterative simulation method is used to determine the configuration of charging facilities based on the number of electric vehicles in the target area, the driving patterns of electric vehicles, and the proportion of electric vehicle types, including: Obtain the number of electric vehicles in the target area, the driving patterns of electric vehicles, and the composition ratio of electric vehicle types, and set the number of Monte Carlo simulations; Set the initial value of the configuration number of switching charging piles to 1 and the initial value of the number of iterations to 1; Monte Carlo simulation is used to obtain the driving pattern data of all electric vehicles in the target area, and the corresponding vehicle model parameters are randomly matched according to the composition ratio of electric vehicle types; the vehicle model parameters include battery capacity, cruising range and charging power of the on-board charger; The charging power of the on-board charger is determined as the charging power of the switching charging pile. According to the driving law data and vehicle model parameters of all electric vehicles in the target area and the configuration number of the switching charging piles, orderly charging control is simulated, and the charging power satisfaction rate of electric vehicles and the load variance index of the distribution network are calculated; If the current value of the number of iterations is less than the number of Monte Carlo simulations, increase the number of iterations by 1 and return to step "obtain the driving law data of all electric vehicles in the target area by using Monte Carlo simulation, and randomly match the corresponding vehicle model parameters according to the composition ratio of electric vehicle types" until the number of Monte Carlo simulations is reached; If the current value of the number of configurations of the switching charging piles is less than the number of electric vehicles in the target area, the number of configurations of the switching charging piles is increased by 1, and the process returns to step "using Monte Carlo simulation to obtain the driving law data of all electric vehicles in the target area, and randomly matching the corresponding vehicle model parameters according to the composition ratio of electric vehicle types", until the number of electric vehicles in the target area is reached; According to the charging capacity satisfaction rate of electric vehicles and the load variance index of the distribution network obtained in each simulation, the optimal configuration quantity and service capacity of the switching charging piles are determined.

10. The charging facility configuration method based on switching charging according to claim 8, characterized in that: When the switching charging pile is a DC charging pile, the configuration quantity of the switching charging pile meets the configuration quantity constraint, and the charging power of the switching charging pile meets the charging power constraint; The expression of the configuration quantity constraint is: N min ≤N≤N max ; The expression of the charging power constraint is: 0<p c ≤P c,max ; Where N represents the number of configurations of the switching charging piles; N min N represents the minimum number of charging facilities required to meet the charging demand of electric vehicles, which is a function of the charging power of the switching charging pile; max Indicates the maximum number of charging facilities; p c Indicates the charging power of the switching charging pile; P c,max Indicates the maximum charging power that an electric vehicle can withstand.

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