A station-network interactive control method for electric vehicle charging station groups

Abstract

The present invention provides a station-network interactive control method for electric vehicle charging station groups, including: S1, modeling the power grid frequency modulation module in the power system, and establishing the generator mathematical model and the load mathematical model respectively; S2, establishing an automatic power generation control model, and determining the components of the generator set and the electric vehicle station group participating in the frequency modulation; S3, based on the generator mathematical model established in step S1, the load mathematical model and the automatic power generation control model established in step S2, calculating the controllable capacity of the electric vehicle; S4, based on the controllable capacity of the electric vehicle calculated in step S3, applying the charging station group to participate in the distribution network frequency modulation strategy, and determining the method of the charging station supporting the power grid frequency. The present invention takes into account the user's willingness and battery capacity, and proposes a distribution method based on the battery charge level, which can reduce the impact of the operation of large-scale cluster charging stations on the power grid and improve the safety of the power grid.

Description

Technical Field

[0001] The invention relates to the field of electric power technology, and in particular to a station-network interactive control method for an electric vehicle charging station group. Background Art

[0002] Due to the intermittent and volatile nature of renewable energy, the access of a large amount of renewable energy to the grid will inevitably have a huge impact on various aspects of the distribution network, such as power quality, distribution network reliability, and distribution network planning.

[0003] Frequency stability is the primary factor for the safe and stable operation of the power grid. Usually, a certain amount of spare capacity will be reserved in the power system, and the system frequency will be kept within the allowable deviation range by limiting power, reducing low frequency load and other means. However, the implementation of these measures may lead to an increase in the operating costs of the system and will also have an impact on the electricity demand of users. In addition to the large-scale random and intermittent energy access in the future, the installed capacity is still expanding, and more grid spare capacity is needed. It is difficult to achieve effective frequency control by conventional power plants alone. If the load can actively participate in the power load balance of the power grid, when the power grid is insufficient, it will actively disconnect part of the load and effectively adjust the active power balance of the power grid, which is conducive to the safe, stable and economical operation of the power grid.

[0004] In the near future, electric vehicles will be fully popularized. In the context of smart grid, the continuous improvement of electric vehicle charging infrastructure provides a good foundation for the friendly interaction between electric vehicles and power grids. Therefore, fully analyzing the charging and discharging characteristics of electric vehicles, formulating corresponding control strategies, and providing auxiliary services for the power grid can not only maintain the safe and stable operation of the power grid, but also has important theoretical and practical significance. Summary of the invention

[0005] The problem to be solved by the present invention is to provide a station-network interactive control method for an electric vehicle charging station group, so as to improve the supporting effect of the cluster charging station on the frequency and voltage of the power grid.

[0006] The objective of the present invention is achieved through the following technical solutions:

[0007] A station-network interactive control method for an electric vehicle charging station group comprises the following steps:

[0008] S1, modeling the grid frequency regulation module in the power system, and establishing the generator mathematical model and the load mathematical model respectively;

[0009] S2, establish an automatic power generation control model to determine the components of generator sets and electric vehicles participating in frequency regulation;

[0010] S3, calculating the controllable capacity of the electric vehicle based on the generator mathematical model and load mathematical model established in step S1 and the automatic power generation control model determined in step S2;

[0011] S4, based on the controllable capacity of the electric vehicle calculated in step S3, the strategy of the charging station group participating in the distribution network frequency regulation is applied to determine the method of the charging station supporting the grid frequency.

[0012] Furthermore, it also includes:

[0013] S5. Based on the generator mathematical model established in step S1, the automatic power generation control model determined in step S2, the electric vehicle controllable capacity calculated in step S3, and the frequency regulation strategy determined in step S4, the electric vehicle charging station group participating in the grid frequency regulation is simulated on the MATLAB / Simulink simulation platform to demonstrate the effectiveness of the proposed method.

[0014] Furthermore, in step S1, a generator mathematical model and a load mathematical model are established respectively, as follows:

[0015] S11: Establishing a mathematical model of the generator

[0016] This is shown in the following equation, which expresses the relationship between the electric and mechanical torques as a function of rotor speed:

[0017] T m -T e =2Hdω / dt

[0018] Where: dω / dt is the generator angular acceleration; H is the inertia constant;

[0019] The relationship between power P and torque T is:

[0020] P=ω r T

[0021] Taking into account the small deviation from the initial value, write:

[0022]

[0023] Thus we get:

[0024] P 0 +ΔP=(ω 0 +Δω r )(T 0 +ΔT)

[0025] When higher-order terms are ignored, the relationship between the disturbance values ​​is:

[0026] ΔP=ω 0 ΔT+T 0 Δω r

[0027] Therefore,

[0028] ΔP-ΔP e =ω 0 (ΔT m -ΔT e )+(T m0 -T e0 )Δω r

[0029] Since the electric torque and mechanical torque are balanced in steady state, T m0 =T e0 , when the speed is expressed in per unit value, ω 0 =1, so we have

[0030] ΔP-ΔP e =ΔT m -ΔT e =2Hdω / dt

[0031] After Laplace transformation, we can get

[0032] ΔP m (s)-ΔP e (s)=2HsΔω r

[0033] S12: Establish load mathematical model

[0034] The dependence of the entire composite load on frequency is:

[0035] ΔP e =ΔP L +DΔω r

[0036] Where: ΔP L is the load change that is insensitive to frequency; DΔω r , is the load change that is sensitive to frequency; D is the load damping constant. The load-damping constant can be expressed as the percentage of load change caused by a 1% frequency change. The typical value of D is 1% or 2%. D=2 means that a 1% frequency change will cause a 2% load change.

[0037] Further, step S2 is specifically as follows:

[0038] When electric vehicles participate in frequency modulation, the regional control deviation omits the filtering link and directly generates a frequency modulation signal through the PI controller; the frequency modulation signal is decomposed in the frequency domain by the Butterworth filter. Assume that the transfer function of the Butterworth low-pass filter is H(ω), and the Butterworth low-pass filter is expressed by the following formula of amplitude squared to frequency:

[0039]

[0040] Where: ω is the signal frequency, ω b is the cut-off frequency; n is the filter order. The higher the order, the faster the amplitude decays in the stop band, and the closer the amplitude-frequency response is to the ideal situation.

[0041] The frequency modulated signal is decomposed into a low-frequency signal and a high-frequency signal by a Butterworth low-pass filter. The low-frequency component is used as the response component of the conventional unit, and the high-frequency component is used as the response component of the electric vehicle station group.

[0042] Further, step S3 is specifically as follows:

[0043] Set the set of electric vehicles in V2G as E VS1 , the set of electric vehicles in unidirectional charging state is E VS2 ,

[0044] The controllable capacity of a single electric vehicle is:

[0045] ΔP 1i =α 1i ·P maxi ,i∈E VS1

[0046] ΔP 2i =α 2i ·min{P bi ,P maxi -P bi},i∈E VS2

[0047] Where: i is E VS1 or E VS2 EV number in the population; P man i is the power limit of charging and discharging of the charging station, P bi For E VS2 The charging reference power of the i-th electric vehicle is the charging power when it does not participate in frequency modulation; α 1i , α 2i ΔP is the user willingness of EV to participate in frequency regulation service. If willing to participate, the value is 1, otherwise it is 0; 1i , ΔP 2i E VS1 Individual and E VS2 Individual frequency modulation capacity, when users are unwilling to participate, i.e., α 1i or α 2i When it is 0, the capacity is 0;

[0048] For E VS1For a vehicle, it is normally in a state of neither charging nor discharging, so the adjustable power is constrained by the maximum power of the charging pile; the system frequency is a normal distribution symmetrical about μ = 50, and the probability of frequency increase and decrease is 50% each. The following formula shows that 0≤P bi -P 2i ≤P bi ≤P bi +ΔP 2i ≤P maxi , the power of an electric vehicle during charging can be [P bi -ΔP 2i ,P bi +P 2i ] interval, ensuring that the charging power is continuously positive and providing equal up and down reserve, SOC is monotonically increasing, and participating in frequency modulation does not affect its normal charging:

[0049]

[0050] Where: C ap1 For E VS1 Dispatchable capacity; C ap2 For E VS2 Dispatchable capacity: The dispatchable capacity is calculated by the cluster charging station and uploaded to the dispatch center to limit the fluctuation of the frequency modulation signal received by the cluster charging station.

[0051] Further, step S4 is specifically as follows:

[0052] According to the frequency modulation capabilities of the two electric vehicle groups, the frequency modulation signals of the two electric vehicle groups are allocated according to the capacity ratio from the dispatchable capacity obtained in step S3. Assume that the frequency modulation signal received by the cluster charging station is u and the frequency is positive when it is increased:

[0053]

[0054] Where: u 1 、u 2 The electric vehicle group E VS1 、E VS2 The frequency modulation response signal;

[0055] After calculating the total frequency modulation power of the two EV groups, the upper stage VS1 , and E VS2 The frequency modulation power borne by electric vehicles is determined according to the battery charge level of each electric vehicle. Signals are sent to electric vehicles through charging piles. Each electric vehicle adjusts the charging base power according to the received signal. When the system frequency is increased, E VS1 Discharge and E VS2To reduce the charging load, vehicles with higher SOC have higher priority and heavier frequency modulation tasks. On the contrary, E VS1 Charging and E VS2 As the charging load increases, the higher the SOC, the lower the priority of the vehicle, and the smaller the frequency modulation task it undertakes. At the same time, considering that the car models in the EV group are different and the battery capacity is different, the power level represented by the same SOC level may not be the same. Therefore, the frequency modulation signal of a single electric vehicle is corrected and the weighted coefficient is established as follows:

[0056]

[0057] Where: γ 1i For E VS1 The weighting coefficient of the FM signal received by the vehicle; E 1i For E VS1 The battery capacity of the i-th EV in , in kW·h; similarly, E VS2 Weighting coefficient γ of the signal received by the vehicle 2i The calculation is the same as above;

[0058] When the system frequency is increased, that is, u ≥ 0:

[0059]

[0060] Where: u 1i , S OC1i E VS1 Frequency modulation power and charge level of electric vehicles in the group; u 2i , S OC2i E VS2 The frequency modulation power and charge level of the electric vehicles in the group;

[0061] When the system frequency is reduced, that is, u<0,

[0062]

[0063] From the above formula, we can see that when the SOC is the same or similar, the EV with a larger battery capacity receives a larger FM power;

[0064] When u≥0,

[0065] u 1j =ΔP 1j ,j∈ψ

[0066]

[0067] When u<0,

[0068] u 1j =-ΔP 1j ,j∈ψ

[0069]

[0070] Where: ψ is the set of vehicles that exceed the power limit. If the result still contains vehicles with power exceeding the limit, repeat the above process until the power of all vehicles is within the limit. Similarly, E VS2 When the power exceeds the limit, the processing process is the same as E VS1 ;

[0071] The grid-side power calculation during the charging and discharging process is as follows:

[0072] P 1i =-Δu 1i ,i∈E VS1

[0073] P 2i =P bi -Δu 2i ,i∈E VS2

[0074] Where: P 1i , ,P 2i Don't be E VS1 With E VS2 The charging and discharging power of the electric vehicle is converted into battery side power and the SOC is calculated:

[0075]

[0076] in,

[0077]

[0078] Where: S OC1i , S OC2i E VS1 With E VS2 SOC in OC1i0 , S OC2i0 The initial state of charge of the electric vehicle; E 2i For E VS2 The capacity of the i-th EV pool; η c , η d are charging efficiency and discharging efficiency respectively;

[0079] Since the initial SOC value of an electric vehicle in each stage of charging will not exceed S OCth , so we only need to satisfy

[0080]

[0081] Where: S OCmax is the maximum value allowed for the charge level, ΔEi is E VS2The amount of electricity added by the i-th electric vehicle in a period of time. Since the effect of frequency modulation on the change of electric vehicle electricity is small and negligible, ΔEi can be calculated by the following formula:

[0082] ΔE i =P bi ×η c ×Δt

[0083] Where: Δt = 30min is the time interval between two similar statistics;

[0084] The charging and discharging management system of cluster charging stations monitors the power grid in real time meas When the grid frequency is abnormal, the charge and discharge management system first determines whether the SOC is within the frequency modulation working range (SOC min SOC max ), if it is not located, the charging and discharging management system of the electric vehicle station group is in a locked state, otherwise it can work normally; secondly, judge f meas The frequency range belongs to. If it is in the FM dead zone (f ref2 , fref1), the cluster charging station is in the hold state, at this time the primary frequency regulation process is determined by the static frequency characteristics of the comprehensive load and the synchronous generator; when f meas When the dead zone is exceeded, the static frequency characteristics of the cluster charging station participate in the primary frequency regulation process of the power grid and share the unbalanced power in the system with the synchronous generator. The expression is as follows:

[0085]

[0086] Where: are the left and right boundaries of the frequency dead zone. When the frequency rises and exceeds the right boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the charging power value to absorb electric energy from the power grid; when the system frequency drops and exceeds the left boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the discharge power value to release electric energy to the power grid.

[0087] When cluster charging stations participate in grid frequency regulation, the relationship curve between grid load disturbance and frequency change is switched. battery The setting controls the slope of the curve of the relationship between grid load fluctuation and frequency change after switching.

[0088] Compared with the existing inventions, the present invention takes into account user willingness and battery capacity, proposes a distribution method based on battery charge level, applies cluster charging stations to participate in distribution network frequency regulation strategy on the basis of the designed controllable capacity of electric vehicles, and proposes a method for charging stations to support grid frequency, which can provide technical support for electric vehicle cluster charging stations to participate in grid frequency regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] Figure 1 This is a flow chart of a station-network interactive control method for an electric vehicle charging station group according to an embodiment of the present invention;

[0090] Figure 2 is a control framework of an embodiment of the present invention;

[0091] Figure 3 is a generator-load model according to an embodiment of the present invention;

[0092] Figure 4 This is a schematic diagram of an electric vehicle participating in frequency modulation according to an embodiment of the present invention;

[0093] Figure 5 is the amplitude-frequency characteristic curve of the Butterworth low-pass filter according to the embodiment of the present invention;

[0094] Figure 6 This is a controllable capacity diagram of an electric vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0095] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0096] See also Figure 1 The embodiment of the present invention provides a station-network interactive control method for an electric vehicle charging station group, which establishes a system model including charging piles participating in frequency modulation. Figure 2 For the control framework of this strategy, an AGC model based on filtering method is established due to the ramp rate limit of the unit and the rapid response characteristics of EV. A power allocation method between individual electric vehicles considering SOC is proposed for AGC transmission signals.

[0097] (S1) Establishing the generator mathematical model and the load mathematical model

[0098] S11: Establishing a mathematical model of the generator

[0099] This is shown in the following equation, which represents the relationship between the electric and mechanical torques as a function of rotor speed.

[0100] T m -T e =2Hdω / dt

[0101] Where: dω / dt is the generator angular acceleration; H is the inertia constant (unit value).

[0102] Regarding the study of load-frequency relationship, mechanical and electric power are generally used instead of torque to express the above relationship. The relationship between power P and torque T is

[0103] P=ω r T

[0104] Taking into account the small deviation (indicated by the prefix △) from the initial value (indicated by the subscript 0), we can write

[0105]

[0106] Thus we can get:

[0107] P 0 +ΔP=(ω 0 +Δω r )(T 0 +ΔT)

[0108] When higher-order terms are ignored, the relationship between the perturbation values ​​can be given as

[0109] ΔP=ω 0 ΔT+T 0 Δω r

[0110] Therefore,

[0111] ΔP-ΔP e =ω 0 (ΔT m -ΔT e )+(T m0 -T e0 )Δω r

[0112] Since the electric torque and mechanical torque are balanced in steady state, T m0 =T e0 When the speed is expressed in per unit value, ω 0 =1, so we have

[0113] ΔP-ΔP e =ΔT m -ΔT e =2Hdω / dt

[0114] After Laplace transformation, we can get

[0115] ΔP m (s)-ΔP e (s)=2HsΔω r

[0116] S12: Establish load mathematical model

[0117] The dependence of the entire composite load on frequency is

[0118] ΔP e =ΔP L +DΔω r

[0119] Where: ΔP L is the load change that is insensitive to frequency; DΔω r , is the load change that is sensitive to frequency; D is the load-damping constant. The load-damping constant can be expressed as the percentage of load change caused by a 1% frequency change. Typical values ​​of D are 1% or 2%. D=2 means that a 1% frequency change will cause a 2% load change. The generator-load model established in the embodiment of the present invention is as follows: Figure 3 shown.

[0120] (S2) Establishing an Automatic Generation Control (AGC) model to determine the components of the generator set and the electric vehicle station group participating in frequency regulation;

[0121] For fast load random disturbances, the generator cannot respond to the frequency modulation signal in time due to its large rotational inertia to achieve a good control effect. Therefore, low-pass filtering is used to reduce noise, and a smooth area control error (ACE) is used to control the power output. When electric vehicles participate in frequency modulation, the AGC system should give full play to its role based on its fast charging and discharging power adjustment characteristics.

[0122] like Figure 4 As shown, ACE omits the filtering link and directly generates the frequency modulated signal through the PI controller. The frequency modulated signal is decomposed in the frequency domain through the Butterworth filter. Assuming the transfer function of the Butterworth low-pass filter is H(ω), the Butterworth low-pass filter can be expressed by the following formula of amplitude squared to frequency:

[0123]

[0124] Where: ω is the signal frequency, ω b is the cut-off frequency; n is the filter order. The higher the order, the faster the amplitude decays in the stop band, and the closer the amplitude-frequency response is to the ideal situation. Figure 5 The frequency response curve in the passband is maximally flat with no fluctuations, while it gradually drops to zero in the stopband.

[0125] The frequency modulation signal can be decomposed into low-frequency signal and high-frequency signal after passing through the filter. Since the response time of traditional units is about tens of seconds, while the response time of electric vehicles is in seconds or even milliseconds, the low-frequency component is used as the response component of conventional units, and the high-frequency component is used as the response component of electric vehicle station groups, thereby effectively improving the frequency modulation effect.

[0126] (S3) calculating the controllable capacity of the electric vehicle based on the mathematical model established in step S1 and the model in step S2;

[0127] Figure 6 For the controllable capacity of electric vehicles, the dispatch center can use probability statistics and other methods to estimate the EV frequency modulation capacity A1 required for a certain period in the future based on the historical operation data of the system. The dispatchable capacity of the cluster charging station in this period is A2. The value of the frequency modulation power signal sent by the dispatch center will not be greater than A1. When A1 is less than or equal to A2, the electric vehicle can participate in frequency modulation. When A1 is greater than A2, sometimes the frequency modulation power signal will be greater than A2. First, the cluster charging station will call all the dispatchable capacity A2. The termination condition of the electric vehicle frequency modulation power allocation of the present invention is that the frequency modulation power of all electric vehicles is within the limit range of individual capacity. When the control signal is too large, the frequency modulation power of the electric vehicle will be limited to the maximum capacity and bear as much frequency modulation power as possible. Then the remaining part of the frequency modulation power needs to be jointly adjusted by conventional units or other types of frequency modulation resources. The capacity of electric vehicles that can participate in frequency control in the two charging states is different, so they need to be calculated separately.

[0128] Set the set of electric vehicles in V2G as E VS1 , the set of electric vehicles in unidirectional charging state is E VS2 .

[0129] The controllable capacity of a single electric vehicle is

[0130] ΔP 1i =α 1i ·P maxi ,i∈E VS1

[0131] ΔP 2i =α 2i ·min{P bi ,P maxi -P bi},i∈E VS2

[0132] Where: i is E VS1 or E VS2 EV number in the population; P max i is the power limit of charging and discharging of the charging station, P bi For E VS2The charging reference power of the i-th electric vehicle is the charging power when it does not participate in frequency modulation; α 1i , α 2i ΔP is the user willingness of EV to participate in frequency regulation service. If willing to participate, the value is 1, otherwise it is 0; 1i , ΔP 2i E VS1 Individual and E VS2 Individual frequency modulation capacity, when users are unwilling to participate, i.e., α 1i or α 2i When it is 0, the capacity is 0. VS1 For a vehicle, it is normally in a state of neither charging nor discharging, so the adjustable power is constrained by the maximum power of the charging pile. The system frequency is a normal distribution symmetrical about μ = 50, and the probability of frequency increase and decrease is 50% each. From the following formula, it can be concluded that 0≤P bi -P 2i ≤P bi ≤P bi +ΔP 2i ≤P maxi , the power of an electric vehicle during charging can be [P bi -ΔP 2i ,P bi +P 2i ] interval to ensure that the charging power is continuously positive and provide equal upward and downward reserve, SOC increases monotonically, and participating in frequency modulation does not affect its normal charging.

[0133]

[0134] Where: C ap1 For E VS1 Dispatchable capacity; C ap2 For E VS2 Dispatchable capacity: The dispatchable capacity is calculated by the cluster charging station and uploaded to the dispatch center to limit the fluctuation of the frequency modulation signal received by the cluster charging station.

[0135] (S4) Based on the controllable capacity of electric vehicles designed in step S3, cluster charging stations are applied to participate in the frequency regulation strategy of the distribution network, and a method for charging stations to support the grid frequency is proposed;

[0136] According to the frequency modulation capabilities of the two electric vehicle groups, the two electric vehicle groups distribute the frequency modulation signal according to the capacity ratio. Assume that the frequency modulation signal received by the cluster charging station is u and the frequency is positive when it is increased.

[0137]

[0138] Where: u 1 、u 2 The electric vehicle group EVS1 、E VS2 FM response signal.

[0139] After calculating the total frequency modulation power of the two EV groups, the upper stage VS1 , and E VS2 The frequency modulation power that electric vehicles bear is determined according to the battery charge level of each electric vehicle, and a signal is sent to the electric vehicle through the charging pile. Each electric vehicle adjusts the charging base power according to the received signal. When the system frequency is increased, E VSl Discharge and E VS2 To reduce the charging load, vehicles with higher SOC have higher priority and heavier frequency modulation tasks. On the contrary, E VS1 Charging and E VS2 As the charging load increases, the higher the SOC, the lower the priority of the vehicle, and the smaller the frequency modulation task it undertakes. At the same time, considering that the car models in the EV group are different and the battery capacity is different, the same SOC level may not represent the same power level. Therefore, the frequency modulation signal of a single electric vehicle can be corrected to establish a weighted coefficient of

[0140]

[0141] Where: γ 1i For E VS1 The weighting coefficient of the FM signal received by the vehicle; E 1i For E VS1 The battery capacity of the i-th EV in , in kW·h. Similarly, E VS2 Weighting coefficient γ of the signal received by the vehicle 2i The calculation is the same as above.

[0142] When the system frequency is adjusted upward, that is, u ≥ 0,

[0143]

[0144] Where: u 1i , S OC1i E VS1 Frequency modulation power and charge level of electric vehicles in the group; u 2i , S OC2i E VS2 Frequency modulation power and charge level of electric vehicles in the group.

[0145] When the system frequency is reduced, that is, u<0,

[0146]

[0147] From the above formula, we can see that when the SOC is the same or similar, the EV with a larger battery capacity receives more frequency modulation power. The third formula means that when the SOC value is the same or similar and within the power limit, the electric vehicle with a larger battery capacity can undertake more frequency modulation tasks. The 30kWh in the formula means that the coefficient is calculated based on an electric vehicle with a battery capacity of 30kWh. If E 1i is 30kWh and α 1i is 1, then γ 1i The value is 1. When the battery capacity of the electric vehicle is greater than 30kWh, the frequency modulation power it bears increases according to the ratio of the battery power; when the battery capacity of the electric vehicle is less than 30kWh, the frequency modulation power it bears decreases according to the ratio of the battery power.

[0148] In addition, the result obtained by the above formula sometimes has a part of the power exceeding the capacity limit ΔP 1i , ΔP 2i In this case, the EV with power exceeding the limit will first limit the frequency modulation power to ΔP 1i , ΔP 2i 、u 1 、u 2 Subtract the power quota of the electric vehicle in full power operation state, and the remaining signal is distributed proportionally among the remaining vehicles. VS1 This situation occurs when u≥0,

[0149] u 1j =ΔP 1j ,j∈ψ

[0150]

[0151] When u<0,

[0152] u 1j =-ΔP 1j ,j∈ψ

[0153]

[0154] Where: ψ is the set of vehicles that exceed the power limit. If the result still contains vehicles with power exceeding the limit, repeat the above process until the power of all vehicles is within the limit. Similarly, E VS2 When the power exceeds the limit, the processing process is the same as E VS1 .

[0155] In the frequency modulation process, electric vehicles not only have power constraints, but also another layer of SOC constraints. SOC is actually the ratio of the integral of the charge and discharge power over time to the battery capacity. Too large or too small a value is not conducive to battery life. To avoid overcharging and over-discharging of the battery, the change of SOC needs to be limited within a certain range. In the above formula: the various powers involved in the calculation are grid-side powers, and energy loss will occur in the interface circuit between the electric vehicle and the grid, i.e., the charging pile, during the charging and discharging process, and the energy cannot be fully converted. In order to ensure the frequency modulation effect, this part of the energy loss is borne by the battery. Therefore, after calculating the grid-side power of charging and discharging, it still needs to be converted into battery-side power to calculate the SOC.

[0156] The grid-side power during the charging and discharging process (assuming charging is positive) is calculated as follows:

[0157] P 1i =-Δu 1i ,i∈E VS1

[0158] P 2i =P bi -Δu 2i ,i∈E VS2

[0159] Where: P 1i , ,P 2i Don't be E VS1 With E VS2 The charging and discharging power of the electric vehicle (grid side) is converted into battery side power and the SOC is calculated.

[0160]

[0161] in,

[0162]

[0163] Where: S OC1i , S OC2i E VS1 With E VS2 SOC in OC1i0 , S OC2i0 The initial state of charge of the electric vehicle; E 2i For E VS2 The capacity of the i-th EV pool; η c , η d They are charging efficiency and discharging efficiency respectively.

[0164] The SOC statistics are uploaded to the cluster charging station every 30 minutes and compared with the threshold S OCthConsidering that the battery power of a vehicle in a charging state will increase significantly within 30 minutes, it should be ensured that the power is not greater than the maximum capacity of the battery itself before reaching the next period, and further prevent it from being overcharged. OCth , so we only need to satisfy

[0165]

[0166] Where: S OCmax is the maximum value allowed for the charge level, ΔEi is E VS2 The amount of electricity added by the i-th electric vehicle in a period of time. Since the effect of frequency modulation on the change of electric vehicle electricity is small and negligible, ΔEi can be calculated by the following formula:

[0167] ΔE i =P bi ×η c ×Δt

[0168] Where: Δt = 30min is the time interval between two similar statistics.

[0169] The charging and discharging management system of cluster charging stations monitors the power grid in real time meas When the grid frequency is abnormal, the charge and discharge management system first determines whether the SOC is within the frequency modulation working range (SOC min SOC max ), if it is not located, the charging and discharging management system of the electric vehicle station group is in a locked state, otherwise it can work normally. meas The frequency range belongs to. If it is in the FM dead zone (f ref2 , fref1), the cluster charging station is in the hold state, at this time the primary frequency regulation process is determined by the static frequency characteristics of the comprehensive load and the synchronous generator; when f meas When the dead zone is exceeded, the static frequency characteristics of the cluster charging station participate in the primary frequency regulation process of the power grid and share the unbalanced power in the system with the synchronous generator. The expression is as follows:

[0170]

[0171] Where: are the left and right boundaries of the frequency dead zone. When the frequency rises and exceeds the right boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the charging power value to absorb electric energy from the power grid; when the system frequency drops and exceeds the left boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the discharge power value to release electric energy to the power grid.

[0172] When cluster charging stations participate in grid frequency regulation, the relationship curve between grid load disturbance and frequency change is switched. battery The setting can control the slope of the curve of the relationship between the load fluctuation and frequency change of the power grid after switching. Within the same load fluctuation range, the steady-state frequency deviation of the power grid is greatly reduced, thereby stabilizing the system frequency within a reasonable range.

[0173] (S5) According to the optimization method proposed in step S4, in order to reduce the impact of large-scale cluster charging station operation on the power grid and improve the safety of the power grid, the power purchase cost and economic benefits of the charging station are comprehensively considered, and a charging and discharging plan for the electric vehicle charging station group participating in the power grid frequency regulation is formulated. A dynamic simulation of the cluster charging station participating in the power system frequency regulation is performed on the MATLAB / Simulink simulation platform. The power system response after the electric vehicle charging station group participates in the frequency regulation and the charging and discharging conditions of the electric vehicle charging station group itself are studied to verify the feasibility and effectiveness of the proposed strategy.

[0174] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A station-network interactive control method for electric vehicle charging station groups, It is characterized in that The steps include: S1, modeling the grid frequency regulation module in the power system, and establishing the generator mathematical model and the load mathematical model respectively; S2, establish the automatic generation control AGC model to determine the components of the generator set and electric vehicle station group participating in frequency regulation; S3, calculating the controllable capacity of the electric vehicle based on the generator mathematical model and load mathematical model established in step S1 and the automatic power generation control model determined in step S2; S4, based on the controllable capacity of the electric vehicle calculated in step S3, applying the strategy of the charging station group participating in the distribution network frequency regulation to determine the method of the charging station supporting the grid frequency; Step S3 is as follows: Set the set of electric vehicles in V2G as E VS1 , the set of electric vehicles in unidirectional charging state is E VS2 , The controllable capacity of a single electric vehicle is: ΔP 1i =a 1i ·P maxi ,i∈E VS1 ΔP 2i =a 2i ·min{P bi ,P maxi -P bi },i∈E VS2 Where: i is E VS1 or E VS2 EV number in the population; P man i is the power limit of charging and discharging of the charging station, P bi For E VS2 The charging reference power of the i-th electric vehicle is the charging power when it does not participate in frequency modulation; α 1i , α 2i ΔP is the user willingness of EV to participate in frequency regulation service. If willing to participate, the value is 1, otherwise it is 0; 1i , ΔP 2i E VS1 Individual and E VS2 Individual frequency modulation capacity, when users are unwilling to participate, i.e., α 1i or α 2i When it is 0, the capacity is 0; For E VS1 For a vehicle, it is normally in a state of neither charging nor discharging, so the adjustable power is constrained by the maximum power of the charging pile; the system frequency is a normal distribution symmetrical about μ = 50, and the probability of frequency increase and decrease is 50% each. The following formula shows that 0≤P bi -P 2i ≤P bi ≤P bi +ΔP 2i ≤P max i , the power of an electric vehicle during charging can be [P bi -ΔP 2i ,P bi +P 2i ] interval, ensuring that the charging power is continuously positive and providing equal up and down reserve, SOC is monotonically increasing, and participating in frequency modulation does not affect its normal charging: Where: C ap1 For E VS1 Dispatchable capacity; C ap2 For E VS2 Dispatchy capacity: The dispatchable capacity is calculated by the cluster charging station and uploaded to the dispatch center to limit the fluctuation of the frequency modulation signal received by the cluster charging station.

2. A station-network interactive control method for an electric vehicle charging station group according to claim 1, It is characterized in that Also includes: S5. Based on the generator mathematical model established in step S1, the automatic power generation control model determined in step S2, the electric vehicle controllable capacity calculated in step S3, and the frequency regulation strategy determined in step S4, the electric vehicle charging station group participating in the grid frequency regulation is simulated on the MATLAB / Simulink simulation platform to demonstrate the effectiveness of the proposed method.

3. A station-network interactive control method for an electric vehicle charging station group according to claim 1, It is characterized in that In step S1, a generator mathematical model and a load mathematical model are established respectively, as follows: S11: Establishing a mathematical model of the generator This is shown in the following equation, which expresses the relationship between the electric and mechanical torques as a function of rotor speed: T m -T e =2Hdω / dt Where: dω / dt is the generator angular acceleration; H is the inertia constant; The relationship between power P and torque T is: P=ω r T Taking into account the small deviation from the initial value, write: Thus we get: P 0 +ΔP=(ω 0 +See r )(T 0 +ΔT) When higher-order terms are ignored, the relationship between the disturbance values ​​is: ΔP=ω 0 ΔT+T 0 Give r Therefore, there is ΔP-ΔP e =ω 0 (ΔT m -ΔT e )+(T m0 -T e0 )See r Since the electric torque and mechanical torque are balanced in steady state, T m0 =T e0 , when the speed is expressed in per unit value, ω 0 =1, so we have ΔP-ΔP e =ΔT m -ΔT e =2Hdω / dt After Laplace transformation, we can get ΔP m (s)-ΔP e (s)=2HsΔω r S12: Establish load mathematical model The dependence of the entire composite load on frequency is: ΔP e =ΔP L +DΔω r Where: ΔP L is the load change that is insensitive to frequency; DΔω r , is the load change that is sensitive to frequency; D is the load damping constant. The load-damping constant can be expressed as the percentage of load change caused by a 1% frequency change. The typical value of D is 1% or 2%. D=2 means that a 1% frequency change will cause a 2% load change.

4. A station-network interactive control method for an electric vehicle charging station group according to claim 1, It is characterized in that Step S2 is specifically as follows: When electric vehicles participate in frequency modulation, the regional control deviation omits the filtering link and directly generates a frequency modulation signal through the PI controller; the frequency modulation signal is decomposed in the frequency domain by the Butterworth filter. Assume that the transfer function of the Butterworth low-pass filter is H(ω), and the Butterworth low-pass filter is expressed by the following formula of amplitude squared to frequency: Where: ω is the signal frequency, ω b is the cut-off frequency; n is the filter order. The higher the order, the faster the amplitude decays in the stop band, and the closer the amplitude-frequency response is to the ideal situation. The frequency modulated signal is decomposed into a low-frequency signal and a high-frequency signal by a Butterworth low-pass filter. The low-frequency component is used as the response component of the conventional unit, and the high-frequency component is used as the response component of the electric vehicle station group.

5. A station-network interactive control method for an electric vehicle charging station group according to claim 1, It is characterized in that Step S4 is specifically as follows: According to the frequency modulation capabilities of the two electric vehicle groups, the frequency modulation signals of the two electric vehicle groups are allocated according to the capacity ratio from the dispatchable capacity obtained in step S3. Assume that the frequency modulation signal received by the cluster charging station is u and the frequency is positive when it is increased: Where: u 1 、u 2 The electric vehicle group E VS1 、E VS2 The frequency modulation response signal; After calculating the total frequency modulation power of the two EV groups, the upper stage VS1 , and E VS2 The frequency modulation power borne by electric vehicles is determined according to the battery charge level of each electric vehicle. Signals are sent to electric vehicles through charging piles. Each electric vehicle adjusts the charging base power according to the received signal. When the system frequency is increased, E VS1 Discharge and E VS2 To reduce the charging load, vehicles with higher SOC have higher priority and heavier frequency modulation tasks. On the contrary, E VS1 Charging and E VS2 As the charging load increases, the higher the SOC, the lower the priority of the vehicle, and the smaller the frequency modulation task it undertakes. At the same time, considering that the car models in the EV group are different and the battery capacity is different, the power level represented by the same SOC level may not be the same. Therefore, the frequency modulation signal of a single electric vehicle is corrected and the weighted coefficient is established as follows: Where: γ 1i For E VS1 The weighting coefficient of the FM signal received by the vehicle; E 1i For E VS1 The battery capacity of the i-th EV in , in kW·h; similarly, E VS2 Weighting coefficient γ of the signal received by the vehicle 2i Calculate the same as above; When the system frequency is increased, that is, u ≥ 0: Where: u 1i , S OC1i E VS1 Frequency modulation power and charge level of electric vehicles in the group; u 2i , S OC2i E VS2 The frequency modulation power and charge level of the electric vehicles in the group; When the system frequency is reduced, that is, u<0, From the above formula, we can see that when the SOC is the same or similar, the EV with a larger battery capacity receives a larger FM power; When u≥0, When u<0, Where: ψ is the set of over-limit vehicles; if the result still contains vehicles with over-limit power, repeat the above process until all vehicle powers are within the limit; similarly, E VS2 When the power exceeds the limit, the processing process is the same as E VS1 ; The grid-side power calculation during the charging and discharging process is as follows: P 1i =-Δu 1i ,i∈E VS1 P 2i =P bi -Δu 2i ,i∈E VS2 Where: P 1i , P 2i Don't be E VS1 With E VS2 The charging and discharging power of the electric vehicle is converted into battery side power and the SOC is calculated: in, Where: S OC1i , S OC2i E VS1 With E VS2 SOC in OC1i0 , S OC2i0 The initial state of charge of the electric vehicle; E 2i For E VS2 The capacity of the i-th EV pool; η c , η d are charging efficiency and discharging efficiency respectively; Since the initial SOC value of an electric vehicle in each stage of charging will not exceed S OCth , so we only need to satisfy Where: S OCmax is the maximum value allowed for the charge level, ΔEi is E VS2 The amount of electricity added by the i-th electric vehicle in a period of time; ΔEi can be calculated by the following formula: ΔE i =P bi ×η c ×Δt Where: Δt = 30min is the time interval between two similar statistics; The charging and discharging management system of cluster charging stations monitors the power grid in real time meas When the grid frequency is abnormal, the charge and discharge management system first determines whether the SOC is within the frequency modulation working range (SOC min SOC max ), if it is not located, the charging and discharging management system of the electric vehicle station group is in a locked state, otherwise it can work normally; secondly, judge f meas The frequency range belongs to. If it is in the FM dead zone (f ref2 , fref1), the cluster charging station is in the hold state, at this time the primary frequency regulation process is determined by the static frequency characteristics of the comprehensive load and the synchronous generator; when f meas When the dead zone is exceeded, the static frequency characteristics of the cluster charging station participate in the primary frequency regulation process of the power grid and share the unbalanced power in the system with the synchronous generator. The expression is as follows: Where: are the left and right boundaries of the frequency dead zone. When the frequency rises and exceeds the right boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the charging power value to absorb electric energy from the power grid; when the system frequency drops and exceeds the left boundary of the frequency dead zone, the electric vehicle station group uses the product of the frequency deviation and the unit regulation power as the discharge power value to release electric energy to the power grid. When cluster charging stations participate in grid frequency regulation, the relationship curve between grid load disturbance and frequency change is switched. battery The setting controls the slope of the curve of the relationship between grid load fluctuation and frequency change after switching.

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