阅读说明：本技术 考虑用户出行需求的电动汽车集群电网调峰容量整合方法 (Electric vehicle cluster power grid peak regulation capacity integration method considering user travel demand ) 是由 王海鑫 袁佳慧 李云路 杨俊友 马一鸣 孙智辉 李延珍 冯佳威 王康 张世宇 于 2021-09-01 设计创作，主要内容包括：本发明涉及考虑用户出行需求的电动汽车集群电网调峰容量整合方法,步骤：进行调峰车辆的筛选；根据车辆SOC值将可调峰类型分类为A类、B类和C类,判断车辆参与调峰状态；根据可调峰类型的分类以及车辆电池充放电功率的上下限,计算电动汽车的可调容量；根据每个电动汽车的可调容量,得到本次循环中第一批充电车辆达到最大电量值时所需的时间t-(d)或放电车辆达到最小电量值时所需的时间t-(u),达到相应时间后将此批车辆退出调峰并返回步骤S1；将新近来车SOC纳入新一轮循环考虑范围,直至调峰阶段结束。本发明通过考虑用户出行需求、汽车电池充放电功率、避免过充过放行为计算电动汽车集群可调峰容量,解决现有技术具有一定局限性的问题。(The invention relates to a peak regulation capacity integration method of an electric vehicle cluster power grid considering user travel demands, which comprises the following steps: screening peak-shaving vehicles; classifying the adjustable peak types into A type, B type and C type according to the SOC value of the vehicle, and judging the state of the vehicle participating in peak adjustment; calculating the adjustable capacity of the electric automobile according to the classification of the adjustable peak types and the upper limit and the lower limit of the charge and discharge power of the vehicle battery; according to the adjustable capacity of each electric automobile, the time t required by the first batch of charging vehicles to reach the maximum electric quantity value in the cycle is obtained d Or the time t required for the discharging vehicle to reach the minimum electric quantity value u When the corresponding time is reached, the batch of vehicles is quitted from peak shaving and returns to the step S1; and (4) taking the SOC of the newly coming vehicle into a new cycle consideration range until the peak shaving stage is finished. The invention calculates the peak-tunable capacity of the electric automobile cluster by considering the travel demand of the user and the charge and discharge power of the automobile battery and avoiding the over-charge and over-discharge behavior,the problem that the prior art has certain limitation is solved.)

1. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid in consideration of the trip demand of a user is characterized by comprising the following steps of: the method comprises the following steps:

s1: according to user input information, user travel requirements and battery capacity constraints are calculated, user responsiveness beta is introduced, a participatable system peak shaving vehicle is obtained, and screening of the peak shaving vehicle is carried out according to judgment conditions of the participatable system peak shaving vehicle;

s2: classifying the tunable peak types into A type, B type and C type according to the SOC value of the vehicle, and judging the state of the vehicle participating in peak regulation;

s3: calculating the adjustable capacity of the electric automobile according to the classification of the adjustable peak types and the upper limit and the lower limit of the charge and discharge power of the vehicle battery;

s4: according to each electric vehicleThe capacity can be adjusted to obtain the time t required by the first batch of charging vehicles to reach the maximum electric quantity value in the cycle_dOr the time t required for the discharging vehicle to reach the minimum electric quantity value_uWhen the corresponding time is reached, the batch of vehicles is quitted from peak shaving and returns to the step S1; while taking into account t_dOr t_uAnd (4) newly coming vehicles exist in the station within the time, the SOC of the newly coming vehicles is brought into a new cycle consideration range, and the peak regulation capacity is calculated again until the peak regulation phase is finished.

2. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid according to claim 1, considering the travel demand of the user, is characterized in that: the formula for calculating the user responsiveness β is:

in the formula, N_EVNumber of electric vehicles to be connected to the charging device, N_V2GThe total number of vehicles willing to participate in the dispatch.

3. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid according to claim 1, considering the travel demand of the user, is characterized in that: the judgment conditions of the participatable system peak shaving vehicle are as follows:

t_sur＞t_r+t_i,chrg+t_y

wherein, t_sur＝t_pre-t_i

In the formula, t_surFor the remaining charging stay time of the vehicle in the current station, t_preTo estimate the time of stayM, t_iIs the current time, t_i，chrgEstimating the charging time for the residual capacity after peak load regulation, t_yThe time margin for getting the vehicle in advance can be set to 30 minutes or more, and the SOC is set_i,tdIndicating the lowest satisfactory electric quantity, SOC, when the vehicle owner leaves_rIs the vehicle residual capacity after peak load regulation, C_i,batIs the battery capacity, P_maxIs the maximum power, eta represents the electric energy conversion efficiency when the electric automobile is charged and discharged, and eta represents the electric energy conversion efficiency when the electric automobile is charged_c50 percent; at time of discharge, η_fIs 80%, SOC_iIs the initial electric quantity when participating in peak regulation, P is the charge-discharge power when participating in peak regulation, t_rIs the peak shaver time.

4. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid according to claim 1, considering the travel demand of the user, is characterized in that: in step S2, class a indicates that SOC is 0-20%, and charging is only possible; b is SOC capacity of 20-80%, which can be charged or discharged; class C has SOC capacity of 80-100%, and can only discharge.

5. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid according to claim 1, considering the travel demand of the user, is characterized in that: in step S3, the adjustable capacity is:

chargeable capacity total amount SOC of class A vehicle in charging station_ADComprises the following steps:

SOC_AD＝η_cP_baset_r·n_A

chargeable capacity total amount SOC of B-type vehicle in charging station_BDComprises the following steps:

SOC_BD＝η_cP_baset_r·n_B

total SOC of dischargeable capacity of class B vehicle in charging station_BUComprises the following steps:

SOC_BU＝η_fP_maxt_r·n_B

total SOC of dischargeable capacity of class C vehicle in charging station_CUIs composed of

SOC_CU＝η_fP_maxt_r·n_C

Chargeable capacity total SOC in charging station_DComprises the following steps:

SOC_D＝SOC_AD+SOC_BD

total SOC of dischargeable capacity in charging station_UComprises the following steps:

SOC_U＝SOC_CU+SOC_BU

in the formula, n_AFor charging the number of class A vehicles, n_BFor charging station class B number of vehicles, n_CFor charging the number of class C vehicles, P_baseTo maintain the bottom power, P_maxIs the maximum power.

6. The method for integrating the peak shaving capacity of the electric vehicle cluster power grid according to claim 1, considering the travel demand of the user, is characterized in that: time t required for the first batch of charging vehicles to reach the maximum electric quantity value in step S4_dComprises the following steps:

time t required for first discharge vehicles to reach minimum electric quantity value_uComprises the following steps:

Technical Field

The invention relates to the technical field of electric vehicle peak shaving capacity integration, in particular to an electric vehicle cluster peak shaving capacity integration method considering user travel demands.

Background

The electric automobile has the characteristics of mobile energy storage, high response speed, high charging and discharging power and the like, and the charging station can utilize the mobile energy storage characteristic to realize the reasonable participation of the large-scale electric automobile in peak shaving response of the power distribution network.

Currently, in the research on the schedulable capacity evaluation of the electric vehicle V2G, when the scheduling capacity provided by the electric vehicle as the controllability load is less considered, it is required to meet the user travel demand, the battery charging and discharging power limitation and avoid the overcharge and overdischarge behaviors. This will reduce the controllable capacity prediction error, cause the electric automobile quantity of the cut-in electric wire netting to fail to meet the scheduling planning, cause economic benefits to reduce.

Disclosure of Invention

The invention provides an electric vehicle cluster peak shaving capacity integration method considering user travel demands, and aims to solve the problem that the number of electric vehicles connected into a power grid cannot meet scheduling planning and economic benefits are reduced because the defect that the peak shaving capacity of multi-influence factors for peak shaving response of electric vehicles is not comprehensively considered in the conventional research.

In order to solve the technical problems, the technical scheme of the invention is as follows:

the method for integrating the peak shaving capacity of the electric vehicle cluster power grid in consideration of the trip demand of a user comprises the following steps:

s1: according to user input information, user travel requirements and battery capacity constraints are calculated, user responsiveness beta is introduced, a participatable system peak shaving vehicle is obtained, and screening of the peak shaving vehicle is carried out according to judgment conditions of the participatable system peak shaving vehicle;

s2: classifying the tunable peak types into A type, B type and C type according to the SOC value of the vehicle, and judging the state of the vehicle participating in peak regulation;

s3: calculating the adjustable capacity of the electric automobile according to the classification of the adjustable peak types and the upper limit and the lower limit of the charge and discharge power of the vehicle battery;

s4: according to the adjustable capacity of each electric automobile, the time t required by the first batch of charging vehicles to reach the maximum electric quantity value in the cycle is obtained_dOr the time t required for the discharging vehicle to reach the minimum electric quantity value_uWhen the corresponding time is reached, the batch of vehicles is quitted from peak shaving and returns to the step S1; while taking into account t_dOr t_uAnd (4) newly coming vehicles exist in the station within the time, the SOC of the newly coming vehicles is brought into a new cycle consideration range, and the peak regulation capacity is calculated again until the peak regulation phase is finished.

Further, the calculation formula of the user responsiveness β is as follows:

in the formula, N_EVNumber of electric vehicles to be connected to the charging device, N_V2GThe total number of vehicles willing to participate in the dispatch.

Further, the judgment conditions of the vehicles capable of participating in the system peak regulation are as follows:

t_sur＞t_r+t_i,chrg+t_y

wherein, t_sur＝t_pre-t_i

In the formula, t_surFor the remaining charging stay time of the vehicle in the current station, t_preTo estimate the residence time, t_iIs the current time, t_i，chrgEstimating the charging time for the residual capacity after peak load regulation, t_yThe time margin for getting the vehicle in advance for the user can be generally set to 30 minutes and above, SOC_i,tdIndicating the lowest satisfactory electric quantity, SOC, when the vehicle owner leaves_rIs the vehicle residual capacity after peak load regulation, C_i,batIs the battery capacity, P_maxIs the maximum power, eta represents the electric energy conversion efficiency when the electric automobile is charged and discharged, and eta represents the electric energy conversion efficiency when the electric automobile is charged_c50 percent; at time of discharge, η_fIs 80%, SOC_iIs the initial electric quantity when participating in peak regulation, P is the charge-discharge power when participating in peak regulation, t_rIs the peak shaver time.

Further, in step S2, the class a is SOC of 0 to 20%, and charging is only possible; b is SOC capacity of 20-80%, which can be charged or discharged; class C has SOC capacity of 80-100%, and can only discharge.

Further, in step S3, the adjustable capacity is:

chargeable capacity total amount SOC of class A vehicle in charging station_ADComprises the following steps:

SOC_AD＝η_cP_baset_r·n_A

chargeable capacity total amount SOC of B-type vehicle in charging station_BDComprises the following steps:

SOC_BD＝η_cP_baset_r·n_B

total SOC of dischargeable capacity of class B vehicle in charging station_BUComprises the following steps:

SOC_BU＝η_fP_maxt_r·n_B

total SOC of dischargeable capacity of class C vehicle in charging station_CUIs composed of

SOC_CU＝η_fP_maxt_r·n_C

Chargeable capacity total SOC in charging station_DComprises the following steps:

SOC_D＝SOC_AD+SOC_BD

total SOC of dischargeable capacity in charging station_UComprises the following steps:

SOC_U＝SOC_CU+SOC_BU

in the formula, n_AFor charging the number of class A vehicles, n_BFor charging station class B number of vehicles, n_CFor charging the number of class C vehicles, P_baseFor maintaining the bottom power, the bottom power P is adopted during the charging of the vehicle_base，P_maxMaximum power, i.e. maximum power P used during discharge_max。

Further, the time t required for the first batch of charging vehicles to reach the maximum electric quantity value in step S4_dComprises the following steps:

time t required for first discharge vehicles to reach minimum electric quantity value_uComprises the following steps:

has the advantages that:

the invention discloses a method for classifying and integrating peak shaving capacity of an electric vehicle cluster by considering user travel demands, and solves the problem that the prior art has certain limitation by calculating the peak shaving capacity of the electric vehicle cluster by considering the user travel demands and the charge and discharge power of a vehicle battery and avoiding overcharge and overdischarge behaviors.

Drawings

Fig. 1 is a flow chart of classification and integration of peak shaving capacity of an electric vehicle cluster considering trip demand of a user;

FIG. 2 is a schematic diagram of vehicle SOC classification;

FIG. 3 is a schematic diagram of an electric vehicle with adjustable margin.

Detailed Description

The technical solution of the present invention is further explained with reference to the drawings and the embodiments.

Fig. 1 is a flowchart of an electric vehicle cluster peak shaving capacity integration method considering user travel demand according to this embodiment.

The method for integrating the peak shaving capacity of the electric vehicle cluster considering the travel demand of the user comprises the following steps:

and S1, performing participatory peak shaving vehicle screening according to the information of the charging predicted leaving time, the minimum SOC satisfaction value when leaving and the like input by the user.

In the embodiment, corresponding charging information is acquired through the vehicle access charging pile, and the remaining charging stay time t of the user is determined through the information such as the leaving time and the minimum SOC satisfaction value input by the user during charging_surAnd the predicted charging time t of the residual electric quantity after peak regulation_i，chrgAnd calculating, and screening out vehicles capable of participating in peak shaving by considering the peak shaving responsiveness of the user.

The calculation process in this step is as follows:

considering that the user responsiveness affects the effect of the final scheduling capacity calculation, the user responsiveness β is introduced to reflect the proportion of users willing to participate in scheduling. The user responsiveness calculation formula is shown in (1).

In the formula N_EVNumber of electric vehicles to be connected to the charging device, N_V2GThe total number of vehicles willing to participate in the dispatch.

When calculating the capacity of the electric automobile participating in peak shaving in the charging station participating in peak shaving, firstly, the remaining charging stay time t of the vehicle in the current station is calculated_surAnd the predicted charging time t of the residual electric quantity after peak regulation_i，chrg. The calculation formulas of the two are shown in (2) - (4).

t_sur＝t_pre-t_i (2)

In the formula t_preTo estimate the residence time, t_iAs the current time

In the formula, SOC_rIs the vehicle residual capacity after peak load regulation, SOC_iIs the electric quantity in peak regulation, P is the charge-discharge power in peak regulation, t_rFor peak shaving time, SOC_i,tdIndicating the lowest satisfactory electric quantity, SOC, when the vehicle owner leaves_i,tCharging with maximum power for the current residual capacity, C_i,batIs the battery capacity.

Judging the remaining charging stay time length and the predicted charging time length of the residual electric quantity of the vehicle under the condition of ensuring the trip demand of the vehicle owner, and setting the ahead vehicle taking time allowance t for preventing the vehicle owner from taking the vehicle in advance_yThe time margin for getting the vehicle ahead can be adjusted according to the requirement and is generally 30 minutes or more, namely the vehicle t_sur＞t_r+t_i,chrg+t_yCan participate in system peak shaving.

S2, screening peak-shaving vehicles according to the above, avoiding damage to batteries of the electric automobile caused by overcharging/overdischarging behaviors, and classifying the peak-shaving types according to the SOC value of the vehicle:

considering that the battery of the electric vehicle is damaged by overcharge or overdischarge, and the battery life is shortened, the battery capacity is classified into three classes ABC. A type: SOC capacity is 0-20%, and charging can only be carried out; b type: the SOC capacity is 20-80%, and the battery can be charged or discharged; class C: the SOC capacity is 80-100%, and only discharge can be carried out. The classification diagram is shown in fig. 2.

S3, considering the upper and lower limits of the charge and discharge power of the vehicle battery, respectively calculating the peak shaving capacity of the electric vehicle according to the charge and discharge conditions of the electric vehicle, and obtaining the electric vehicle cluster classification peak shaving capacity considering the travel demand of the user, wherein the calculation process is as follows:

the schedulable capacity of the electric automobile is considered to be limited by factors such as user charge and discharge power, an adjustable upper limit and an adjustable lower limit, and the electric automobile cannot be scheduled without limit. The schematic diagram of the adjustable margin is shown in fig. 3.

The horizontal line area is a feasible area defined by state variable constraint, the curve represents the electric quantity of the electric automobile, the feasible area of the electric automobile takes the point corresponding to the electric quantity and the charging moment when the electric automobile is connected as a starting point A, and the slope of the area edge AB is the maximum power P_maxThe slope of the side AC is the guaranteed bottom power P_baseThe triangle formed by the straight lines of the maximum possible electric quantity is shown as the hatched area.

In step S3, the adjustable capacity is divided into two cases, one case is the discharge capacity SOC of the single electric vehicle in unit time_mThe other condition is the charging capacity SOC of the single electric automobile in unit time_b，

Discharge capacity SOC of single electric automobile in unit time_mComprises the following steps:

SOC_m＝η_fP_maxt

charging capacity SOC of single electric automobile in unit time_bComprises the following steps:

SOC_b＝η_cP_baset

in the formula eta_cEfficiency of electric energy conversion, eta, for charging electric vehicles_c＝50％η；η_fEfficiency of electric energy conversion, eta, for electric vehicles when discharging_fWhere η is 80% η, η represents the electric energy conversion efficiency when the electric vehicle is charged and discharged.

Chargeable capacity total amount SOC of class A vehicle in charging station_ADAs shown in (7).

SOC_AD＝η_cP_baset_r·n_A (7)

Chargeable capacity total amount SOC of B-type vehicle in charging station_BDAs shown in (8).

SOC_BD＝η_cP_baset_r·n_B (8)

Total SOC of dischargeable capacity of class B vehicle in charging station_BUAs shown in (9).

SOC_BU＝η_fP_maxt_r·n_B (9)

Total SOC of dischargeable capacity of class C vehicle in charging station_CUAs shown in (10).

SOC_CU＝η_fP_maxt_r·n_C (10)

Chargeable capacity total SOC in charging station_DAs shown in (11).

SOC_D＝SOC_AD+SOC_BD (11)

Total SOC of dischargeable capacity in charging station_UAs shown in (12).

SOC_U＝SOC_CU+SOC_BU (12)

In the formula, n_AThe number of class A vehicles in the charging station, n_BThe number of B-type vehicles in the charging station, n_CThe number of class C vehicles in the charging station.

S4: avoiding the occurrence of overcharge/overdischarge behaviors and obtaining the time t required by the first batch of charging vehicles to reach the maximum electric quantity value in the cycle_dOr the time t required for the discharging vehicle to reach the minimum electric quantity value_uAnd after reaching the corresponding time, the batch of vehicles is quitted from peak shaving and returns to the step S1. While taking into account t_dOr t_uAnd (4) newly coming vehicles exist in the station within the time, the SOC of the newly coming vehicles is brought into a new cycle consideration range, and the peak regulation capacity is calculated again until the peak regulation phase is finished. The specific calculation method is as follows:

the time td required for the first batch of charged vehicles to reach the maximum charge value is shown as (13).

Time t required for first discharge vehicles to reach minimum electric quantity value_uAs shown in (14).

In the formula, SOC_iIs the initial electric quantity when participating in peak shaving.

In the embodiment, in the process of calculating the participatory peak shaving capacity of the electric automobile cluster, the user inputs the information of the predicted leaving time of the user during charging, the minimum SOC satisfaction value during leaving and the like by the user when the vehicle is connected into the charging pile, and then the participatory peak shaving vehicles are screened by considering the user responsiveness and the user travel demands, so that the future peak shaving capacity prediction accuracy can be effectively improved, the controllable capacity prediction error is reduced, and the quantity of the electric automobiles connected into a power grid is ensured to meet the scheduling plan.

In the embodiment, the SOC of the vehicle participating in peak shaving is classified, so that an overcharge and overdischarge event is avoided, and the service life of the battery of the vehicle participating in peak shaving is guaranteed.