Virtual power plant power control method based on electric vehicle response priority sequence

Abstract

The present invention discloses a virtual power plant power control method based on an electric vehicle response priority sequence, which determines the power target value and response time period of electric vehicles participating in demand response, determines the power response capability of electric vehicles that changes over time; determines the power target value of the current time interval according to the power response capability of the electric vehicle; calculates the response time margin index RTM of each electric vehicle monomer in the current time interval, and establishes an electric vehicle response priority sequence; distributes and issues electric vehicle charging and discharging power instructions, and checks whether the power target value is reached after execution; recalculates the electric vehicle response priority sequence and distributes power instructions in the next time interval, and traverses each time interval. This method takes into account the performance decay of electric vehicle batteries and user needs, ensures user travel experience, and can effectively improve the efficiency of electric vehicle resources participating in power response in virtual power plants and the enthusiasm of users to participate in demand response.

Description

Technical Field

[0001] The invention relates to a virtual power plant power control method based on an electric vehicle response priority sequence, and belongs to the technical field of virtual power plants. Background Art

[0002] With the continuous advancement of my country's energy transformation, the power system has posed new challenges to the functions and operation of the power grid. The randomness, intermittency and volatility of renewable energy such as wind and solar energy have brought huge peak load regulation pressure to the power grid. At the same time, with the increase in the number of electric vehicles in my country, the disorderly charging of a large number of electric vehicles has brought huge peak load pressure to the power grid. According to statistics, every time the proportion of electric vehicles increases by 20%, the system peak demand will increase by nearly 10%. If issues such as system spare capacity are considered, the redundancy of the transmission and distribution system must be increased by 20%. Electric vehicles are connected to the power grid through charging piles. The input end of the charging pile is directly connected to the AC power grid. The output end of the charging pile is equipped with a charging plug for charging electric vehicles. Generally, two charging methods are provided: conventional charging and fast charging.

[0003] The existing power control strategies of virtual power plants for electric vehicles participating in grid demand response do not fully consider the particularity of electric vehicles as a means of transportation. They are usually treated as distributed energy storage batteries and ignore the performance degradation of electric vehicle batteries after a large number of disordered charging processes. They participate in the response with unified constant power charging and discharging control, which often fails to fully tap the potential of electric vehicle batteries. It also affects the user's travel experience and reduces the user's enthusiasm for participating in demand response. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a virtual power plant power control method based on an electric vehicle response priority sequence.

[0005] To achieve the above-mentioned object, the present invention provides a virtual power plant power control method based on an electric vehicle response priority sequence, comprising: obtaining virtual power plant data, the virtual power plant data including basic information of electric vehicles, expected vehicle use time of users, minimum state of charge of electric vehicles to meet user travel needs, electric vehicle access time and initial state of charge information of electric vehicles; determining the power target value and response time period of electric vehicle clusters participating in the response according to the total power of the virtual power plant participating in the demand response;

[0006] Conduct personalized modeling based on the historical charging and discharging data of electric vehicles to obtain the charging and discharging curve of electric vehicle monomers;

[0007] The response time period is divided into multiple time intervals of equal length, and the response capability of the electric vehicle monomer is calculated according to the constraint conditions and the charge and discharge curve of the electric vehicle monomer;

[0008] According to the electric vehicle cluster aggregation response capability and the power target value of the electric vehicle cluster participating in the response, the power target value of the electric vehicle cluster in each time interval is set;

[0009] According to the minimum state of charge of electric vehicles to meet the travel needs of users, the response time margin index RTM of electric vehicle monomers is calculated;

[0010] Establishing an electric vehicle response priority sequence based on the RTM, the current state of charge of the electric vehicle, and the power target value of the electric vehicle cluster in a single time interval;

[0011] Starting from the current time interval, the electric vehicle response priority sequence is updated cyclically and iteratively at the beginning of each time interval, and the power target value of each single electric vehicle is allocated and sent to the corresponding charging pile for execution until the response time period ends.

[0012] Preferably, personalized modeling is performed based on the historical charging and discharging data of electric vehicles to obtain the charging and discharging curve of electric vehicle monomers, including:

[0013] The current formula for the electric vehicle battery is:

[0014]

[0015] In the formula, The current value required at time t to respond to the charge and discharge curve of the electric vehicle monomer n times, n-1 represents the number of times the electric vehicle battery charge and discharge has responded;

[0016] Obtaining the state of charge of an electric vehicle cell when it is being charged based on the current value;

[0017] Based on the initial state of charge information of the electric vehicle and the real-time state of charge of the electric vehicle during charging, a charge and discharge curve of the electric vehicle monomer is established;

[0018] In the electric vehicle single-cell charge and discharge curve, according to the minimum state of charge of the electric vehicle to meet the user's travel needs and the maximum state of charge of the electric vehicle to meet the user's travel needs, the lower boundary line of the real-time state of charge of the electric vehicle when charging and the upper boundary line of the real-time state of charge of the electric vehicle when charging are constructed. The upper boundary line and the lower boundary line of the real-time state of charge of the electric vehicle when charging are the feasible domain of charging and discharging of the electric vehicle. The horizontal axis is the charging time, and the vertical axis is the state of charge of the electric vehicle when charging.

[0019] S min is the minimum state of charge value of the electric vehicle, S eis the minimum state of charge of electric vehicles to meet the travel needs of users when off-grid, S s It is the initial state of charge information of the electric vehicle;

[0020] When S s ≤S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging until the state of charge of the electric vehicle monomer reaches S min ;

[0021] When S s >S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging until the real-time state of charge of the electric vehicle reaches [S e ,S max ].

[0022] Preferably, the constraints include:

[0023] The charging power or discharging power of electric vehicles needs to meet the following requirements:

[0024] P(t)=m c (t)P c η c -m d (t)P d / η d ,

[0025] Where: P(t) is the real-time charging power or discharging power of the electric vehicle, P c is the real-time charging power of the electric vehicle, P d is the real-time discharge power of the electric vehicle, η c is the charging efficiency of electric vehicles, η d is the discharge efficiency of electric vehicles; m c (t) is the online charging status of the electric vehicle, m c (t) = 1 means it is in charging state, m c (t) = 0 means it is in the non-charging state; m d (t) is the discharge state of the electric vehicle, m d (t) = 1 means it is in the discharge state, m d (t) = 0 means it is in the non-discharging state, m c (t)+m d (t)≤1; When charging an electric vehicle, the following conditions must be met:

[0026]

[0027] E min ≤E(t)≤Emax ,

[0028]

[0029]

[0030] Where S(t) is the real-time state of charge of the electric vehicle when charging, t s The starting moment of charging the electric vehicle, B e is the battery capacity of the electric vehicle, E(t) is the real-time power of the electric vehicle, and E s is the initial charge of the electric vehicle, E max is the maximum amount of electricity that an electric car can hold, E min is the minimum amount of electricity that an electric vehicle can hold, is the maximum charging power of the electric vehicle, P c is the actual charging power of the electric vehicle, is the maximum discharge power of the electric vehicle, P d is the actual discharge power of the electric vehicle; the upper and lower boundaries of the power of the electric vehicle when charging a single unit must meet the following requirements:

[0031] E up (t)=min(E(t),E max ), t∈(t s ,t d )

[0032] E dn (t)=max(E(t),E min )

[0033]

[0034] In the formula, E up (t) is the maximum amount of electricity when the electric vehicle is charged at time t, E dn (t) is the minimum power value of the electric vehicle when charging at time t, E e The initial charge when charging an electric vehicle, t s and t d is a constant, t s <t d , t d The moment to stop charging your electric car.

[0035] Preferably, the response time period is divided into a plurality of time intervals of equal length, and the response capability of the electric vehicle monomer is calculated according to the constraint conditions and the charge and discharge curve of the electric vehicle monomer, including:

[0036] Based on the feasible domain of electric vehicle charging and discharging, the single-cell response capability of electric vehicles is calculated:

[0037] The response time period [t1, t2] is divided into m time periods of length Δt, t1 and t2 are constants, t1+Δt≤t2, m=(t2-t1) / Δt, and the charging power of the electric vehicle remains unchanged within Δt, then:

[0038]

[0039] Where, E(t) is the real-time power of the electric vehicle, E s is the initial power of the electric vehicle when it is charged, P(k) is the current charging power of the electric vehicle, v(k) indicates whether the electric vehicle is charged online in the kth time period, k∈[1,m], v(k)=1 indicates online charging, and v(k)=0 indicates offline not charging;

[0040] The maximum charging power that can be increased or reduced for an electric vehicle unit is:

[0041]

[0042]

[0043] Where P + (k) represents the maximum charging power that can be increased for an electric vehicle unit, P - (k) represents the maximum reducible charging power of an electric vehicle; To consider the maximum power range that can be increased by power constraints, E up (k+1)-E(k) is the maximum chargeable power of the electric vehicle in the kth period, (E up (k+1)-E(k)) / Δt+P(k) is the impact of power constraints reflected by the rechargeable potential of electric vehicle monomers under current working conditions, E up (k+1) is the upper limit of the electric vehicle's battery capacity at the beginning of the k+1th period, is the maximum discharge power of the electric vehicle, E(k) is the electric vehicle power at the beginning of the kth period, E dn (k+1) is the lower limit of the electric vehicle's single power at the beginning of the k+1th period;

[0044] The maximum charging power that can be increased or reduced by an electric vehicle cluster is:

[0045]

[0046]

[0047] Where: The maximum charging power that can be increased for an electric vehicle cluster. is the maximum charging power that can be reduced by the electric vehicle cluster, N is the total number of electric vehicle monomers in the electric vehicle cluster, i∈[1,N]; P + (i,k) is the maximum power that can be increased by the i-th electric vehicle unit in the k-th period, P - (i,k) is the maximum power that can be reduced for the i-th electric vehicle unit in the k-th time period.

[0048] Prioritize the calculation of the electric vehicle monomer response time margin indicator RTM:

[0049]

[0050] Where RTM is the response time margin index of electric vehicle monomer, which represents the difference between the remaining parking time and the necessary charging time of electric vehicle monomer; S i (t) is the state of charge value of the i-th electric vehicle at time t, is the off-grid time of the i-th electric vehicle, is the expected state of charge of the ith electric vehicle when it is off-grid, S i (t) is the charge state of the ith electric vehicle at time t, Q i is the battery capacity of the i-th electric vehicle, is the SOC of the i-th electric vehicle when it joins the grid, is the time when the i-th electric car joins the grid.

[0051] Preferably, an electric vehicle response priority sequence is established based on the RTM, the current state of charge of the electric vehicle and the power target value of the electric vehicle cluster in a single time interval, including:

[0052] Step 1: Collect the state of charge of electric vehicles at time t1 and calculate the initial electric vehicle cluster aggregation response capability;

[0053] Step 2: Within the EV cluster aggregate response capability, set the EV cluster power target value P within the response time period [t, t+Δt] S , according to the dispatching instructions, filter and regulate electric vehicles, and obtain the electric vehicle priority queue response system dispatch:

[0054] When the dispatch instruction requires the electric vehicle cluster to increase the response power, the corresponding electric vehicles are sequentially stopped from discharging in descending order according to the RTM values. When the RTM values ​​are the same, the electric vehicles with a smaller state of charge are given priority to stop discharging. When all electric vehicles stop discharging and the need for the electric vehicle cluster to increase the response power is still not met, the corresponding electric vehicles are sequentially charged in ascending order according to the RTM values. When the RTM values ​​are the same, the electric vehicles with a smaller state of charge are given priority to start charging.

[0055] When the dispatch instruction requires the electric vehicle cluster to reduce the response power, the corresponding electric vehicles are stopped charging in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicles with a large state of charge are stopped charging first. When all electric vehicles stop charging and still cannot meet the electric vehicle cluster's response power reduction demand, the corresponding electric vehicles are started to discharge in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicles with a large state of charge are started to discharge first.

[0056] Step 3: According to the generated electric vehicle priority queue response system scheduling, check whether the response power P of the electric vehicle reaches the power target value P S , if the power target value P is reached S Then the operation is terminated, otherwise the real-time state of charge of the electric vehicle and the charging state of the electric vehicle at time t are updated according to the electric vehicle priority queue response system scheduling within [t, t+Δt];

[0057] Step 4: Increase the value of t by Δt and run step 2.

[0058] Prioritize access to virtual power plant data, including:

[0059] Users register on the virtual power plant management and control system platform and enter basic information about electric vehicles;

[0060] The user inputs the expected time of use of the vehicle and the minimum state of charge of the electric vehicle that satisfies the user's travel needs on the mobile client;

[0061] The basic information of electric vehicles includes the production time of the electric vehicle, the battery capacity of the electric vehicle and the model of the electric vehicle.

[0062] Prioritize and distribute the power target value P of each electric vehicle S Execute the corresponding charging pile until the response time period ends, including:

[0063] Allocate and sequentially send the power target value of each electric vehicle to the corresponding charging pile for execution;

[0064] (1) If the power target value P S If it is greater than the P(t) of the current electric vehicle monomer, the electric vehicle monomers discharging to the grid through the charging pile will be issued a stop discharge command one by one according to the RTM values ​​of the electric vehicle monomers from large to small, and the real-time charging power of the electric vehicle monomers will be 0;

[0065] If there is no electric vehicle unit in the electric vehicle cluster that is in a discharging state and the current electric vehicle unit's P(t) <P SIf the value of the RTM value of the electric vehicle monomer is established, charging instructions are issued to the electric vehicle monomers one by one in ascending order, and the real-time charging power of the electric vehicle monomer is the maximum charging power of the monomer. Electric vehicle monomers with the same RTM value are accepted and executed in order of the state of charge from the smallest to the largest;

[0066] After the current electric vehicle monomer successfully starts charging, check the P(t) of the current electric vehicle monomer <P S Is it established? If so, continue to issue the next electric vehicle single power target value;

[0067] If the power target value P S If the power is less than the real-time power P(t), the stop charging command is issued to each electric vehicle monomer in descending order according to the RTM value of the electric vehicle monomer, and the real-time charging power of the electric vehicle monomer is 0;

[0068] When there is no electric vehicle in the charging state in the electric vehicle cluster and P(t)>P S If the RTM value of the electric vehicle is established, the electric vehicle monomers connected to the charging piles in the electric vehicle cluster are issued discharge instructions one by one in descending order. The real-time charging power of the electric vehicle monomer is the maximum discharge power of the monomer.

[0069] Electric vehicle monomers with the same RTM value receive and execute discharge instructions in descending order according to the charge state of the electric vehicle monomers;

[0070] After each discharge instruction is issued and executed successfully, it is determined that the electric vehicle cluster P(t)>P S Is it established? If so, continue to issue the next single power target value of the electric vehicle.

[0071] The beneficial effects achieved by the present invention are:

[0072] The present invention takes into account the battery characteristic attenuation caused by multiple charging and discharging of actual electric vehicles and the time-varying power during the charging and discharging process. The electric vehicle response capability obtained through model iteration and time discretization processing is more accurate. On this basis, an electric vehicle response priority sequence is established for power control to achieve the required target power without affecting the user's travel experience. At the same time, the number of unnecessary response charging and discharging times of the electric vehicle battery is reduced, thereby improving the service life of the electric vehicle battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 The S in the present invention S >S min Schematic diagram of the maximum controllable charging and discharging area of ​​an electric vehicle cell;

[0074] Figure 2 The S in the present invention S ≤S min Schematic diagram of the maximum controllable charging and discharging area of ​​an electric vehicle cell;

[0075] Figure 3 is a schematic diagram of the remaining uncharged power of the i-th electric vehicle monomer at time t of the present invention;

[0076] Figure 4 is a flow chart of establishing an electric vehicle response priority sequence according to the present invention;

[0077] Figure 5 is a flow chart of the present invention;

[0078] Figure 6 It is a module schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0079] The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and are not intended to limit the protection scope of the present invention.

[0080] It should be noted that if there are directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention, they are only used to explain the relative position relationship and movement status of the various components under a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0081] In addition, if the descriptions of "first" and "second" etc. are involved in the present invention, they are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0082] A virtual power plant power control method based on electric vehicle response priority sequence, comprising:

[0083] Collecting virtual power plant data, including basic information of electric vehicles, real-time information of electric vehicles, time of electric vehicle access to the grid, state of charge information of electric vehicles, minimum state of charge of electric vehicles to meet user travel needs, etc.;

[0084] According to the power response target value issued by the dispatching system, determine the electric vehicle cluster response target power and response time period;

[0085] Carry out personalized modeling of electric vehicles and obtain the charge and discharge curve of electric vehicle monomers based on historical charge and discharge data;

[0086] The response time window is divided into multiple time intervals of equal length, and the response capability of a single electric vehicle in each time interval is calculated according to the constraint conditions and the charge and discharge curve of the electric vehicle, so as to obtain the aggregated response capability of the electric vehicle cluster;

[0087] According to the electric vehicle cluster aggregation response capability and response target power, the electric vehicle cluster power control target within a single time interval is set;

[0088] Calculate the response time margin index RTM of each electric vehicle according to the user's travel demand, and establish the electric vehicle response priority sequence according to RTM, the current state of charge of the electric vehicle and the power control target value of the electric vehicle cluster within a set single time interval;

[0089] According to the electric vehicle response priority sequence in the current time interval, the power control target value of each electric vehicle is sent to the corresponding charging pile for execution; at the beginning of the next time interval, the electric vehicle response priority sequence is updated and the power control target value of each electric vehicle is sent to the corresponding charging pile for execution, and the process is iterated until the response time window ends, completing the power response process. Obtaining virtual power plant data includes the following steps:

[0090] (1) When a user registers on the virtual power plant management and control system platform (such as the virtual power plant supporting APP or WeChat public account), the basic information of electric vehicles as controllable resources will be entered into the platform database.

[0091] (2) When a user receives the demand response plan information published on the virtual power plant supporting APP or WeChat official account, he / she confirms whether to participate in the virtual power plant power response through the mobile client (such as the virtual power plant supporting APP or WeChat official account), and enters the expected vehicle usage time and minimum travel charge state requirements according to the travel plan. The virtual power plant management and control system background associates the user input information with the corresponding electric vehicle resources.

[0092] 3. Personalized modeling of electric vehicles includes:

[0093] The state of charge range of the electric vehicle battery is set to 10% to 90%. Depending on the type of electric vehicle battery, the upper and lower limits of the state of charge may be different.

[0094] The electric vehicle battery is simplified to constant voltage charging. The charge and discharge current gradually decreases over time and the battery characteristics decay as the number of uses increases. A storage battery charge / discharge curve modeling method based on historical data is adopted. The current calculation formula is:

[0095]

[0096] in The current value at time t required to respond to n charge / discharge curves, and n-1 represents the number of times the electric vehicle battery has responded to charge / discharge.

[0097] Establish the feasible domain of electric vehicle charging and discharging Figure 1 and Figure 2 As shown, Figure 1 and Figure 2 The meanings of the variables are as follows:

[0098] S max : The maximum state of charge value of an electric vehicle monomer, which is 100%;

[0099] S min : The minimum state of charge value of the electric vehicle is set to avoid excessive discharge and damage to the battery life, and the value is 20%;

[0100] S e : The minimum state of charge of electric vehicles to meet the travel needs of users when off-grid;

[0101] S s It is the initial state of charge information of the electric vehicle;

[0102] td is the maximum charging time;

[0103] Figure 1-2 Medium s is the initial charging time; Figure 2 Medium min The state of charge of the electric vehicle reaches S min Charging time;

[0104] As a means of transportation, electric vehicles should first meet the various travel needs of users. Depending on the initial power of the electric vehicle when it is first connected to the power grid, there are two feasible charging and discharging domains as shown in the figure.

[0105] (a) When S s >S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging until the real-time state of charge of the electric vehicle reaches [S e ,S max ]; the lower boundary line of the real-time state of charge of the electric vehicle when charging and the upper boundary line of the real-time state of charge of the electric vehicle when charging are the feasible domain of the electric vehicle's charging and discharging. The controllable charging and discharging area of ​​the electric vehicle is as follows: Figure 1 The shaded area in the figure is shown. Figure 2 In the ts The SOC connected to the grid at any time is S s (Point A), and immediately at rated power P e Start charging, the upper boundary of the corresponding controllable area is point A-point B-point C; if the rated power P is immediately e Start discharging, the corresponding lower boundary of the controllable area is point A-point F-point E. In addition, to ensure that the SOC can reach the minimum value S of the battery power required by the electric vehicle user when leaving the grid e The ED segment indicates that it needs to be forced to charge before traveling, and there are multiple paths available in the feasible domain.

[0106] (b) When S s ≤S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging to S min , before this, electric vehicles do not have the ability to respond to regulation, and after that (a) is consistent.

[0107] Gain electric vehicle cluster aggregation response capabilities, including:

[0108] Based on the feasible domain of electric vehicle charging and discharging, the single-cell response capability of electric vehicles is calculated:

[0109] Divide a response time window [t1, t2] into m time periods of length Δt, m = (t2-t1) / Δt, and the charging power of the electric vehicle remains unchanged within Δt, then:

[0110]

[0111] Where, E(t) is the real-time power of the electric vehicle, E s is the initial power of the electric vehicle, P(k) is the current charging power of the electric vehicle, v(k) indicates whether the electric vehicle is online in the kth time period, k∈[1,m], v(k)=1 indicates online, v(k)=0 indicates offline;

[0112] The maximum charging power that can be increased or reduced for an electric vehicle unit is:

[0113]

[0114]

[0115] Where: P + (k) represents the maximum charging power that can be increased for an electric vehicle unit, P - (k) represents the maximum reducible charging power of an electric vehicle; To consider the maximum power range that can be increased by power constraints, E up(k+1)-E(k) is the maximum chargeable power of the electric vehicle in the kth period, (E up (k+1)-E(k)) / Δt+P(k) is the impact of power constraints reflected by the rechargeable potential of electric vehicle monomers under current working conditions. is the maximum charging power of electric vehicle monomer, E up (k+1) is the upper limit of the electric vehicle's battery capacity at the beginning of the k+1th period, is the maximum discharge power of the electric vehicle, E(k) is the electric vehicle power at the beginning of the kth period, E dn (k+1) is the lower limit of the electric vehicle's single power at the beginning of the k+1th period;

[0116] The discharge of electric vehicle monomers can be regarded as the reduction of charging power. By comparing constraints such as power boundary and power boundary, the maximum increase / reduction power of electric vehicle monomers in each period is calculated.

[0117] (2) The maximum charging power that can be increased or reduced by an electric vehicle cluster:

[0118]

[0119]

[0120] Where: The maximum charging power that can be increased for an electric vehicle cluster. is the maximum charging power that can be reduced by the electric vehicle cluster, N is the total number of electric vehicle monomers in the electric vehicle cluster, i∈[1,N]; P + (i,k) is the maximum power that can be increased by the i-th electric vehicle unit in the k-th period, P - (i,k) is the maximum power that can be reduced for the i-th electric vehicle unit in the k-th time period.

[0121] The constraints include:

[0122] (1) Power boundary

[0123] The charging / discharging power calculation formula of electric vehicles is as follows:

[0124] P(t)=m c (t)P c η c -m d (t)P d / η d

[0125] Where: P c is the real-time charging power of the electric vehicle, P d is the real-time discharge power of the electric vehicle, ηc is the charging efficiency of electric vehicles, η d Discharge efficiency of electric vehicles; m c (t) is the online charging status of the electric vehicle, m c (t) = 1 means it is in charging state, m c (t) = 0 means it is in the non-charging state; m d (t) is the discharge state of the electric vehicle, m d (t) = 1 means it is in the discharge state, m d (t) = 0 means it is in the non-discharging state; m c (t)+m d (t)≤1.

[0126] (2) Electricity boundary:

[0127] The power boundary is represented by the maximum / minimum power. The boundary is in dynamic change at each moment. Changes in the previous scheduling process will also cause changes in the subsequent power boundary.

[0128] The impact of the power boundary on EV responsiveness must satisfy:

[0129]

[0130] E min ≤E(t)≤E max

[0131]

[0132]

[0133] Where S(t) is the real-time SOC of the electric vehicle, B e is the battery capacity of the electric vehicle, E(t) is the real-time power of the electric vehicle, E s is the initial charge of the electric vehicle, E max is the maximum power of the electric vehicle, E min is the minimum value of the electric vehicle’s power, is the maximum charging power of the electric vehicle, P c is the actual charging power of the electric vehicle, is the maximum discharge power of the electric vehicle, P d is the actual discharge power of the electric vehicle;

[0134] The upper and lower limits of the power of a single EV are as follows:

[0135] E up (t)=min(E(t),E max ), t∈(t s ,td )

[0136] E dn (t)=max(E(t),E min )

[0137] In the formula, E up (t) is the maximum amount of electricity when the electric vehicle is charged at time t, E dn (t) is the minimum power value of the electric vehicle when charging at time t, t s and t d is a constant, t s <t d .

[0138] 3. The steps to establish a response priority queue include:

[0139] Step 1: Determine the response capability evaluation time window [t1, t2], and calculate the initial response capability of the electric vehicle cluster by collecting the single electric vehicle state data at time t1;

[0140] Step 2: Within the EV cluster aggregate response capability, set the target power value P of the EV cluster response system within the response time window [t, t+Δt] S , according to the dispatching instructions, filter and regulate electric vehicles, and obtain the electric vehicle priority queue response system dispatch:

[0141] When the dispatch instruction requires the electric vehicle cluster to increase the response power, the discharge power of the electric vehicle is reduced first, and the corresponding electric vehicles are stopped from discharging in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicles with smaller state of charge are stopped first; when all electric vehicles stop discharging and still cannot meet the electric vehicle cluster's increased response power demand, the electric vehicles are started to be charged, and the corresponding electric vehicles are charged in order from small to large RTM values. When the RTM values ​​are the same, the electric vehicles with smaller state of charge are started to be charged first;

[0142] When the dispatch instruction requires the electric vehicle cluster to reduce the response power, the charging power of the electric vehicle is reduced first, and the corresponding electric vehicles are stopped charging in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicle with a large state of charge is stopped charging first. When all electric vehicles stop charging and still cannot meet the electric vehicle cluster's response power reduction requirements, the electric vehicle starts discharging, and the corresponding electric vehicles are started discharging in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicle with a large state of charge is started discharging first.

[0143] Step 3: According to the generated electric vehicle priority queue response system scheduling, check whether the response power P of the electric vehicle reaches the target power setting value PS , according to the electric vehicle priority queue response system scheduling within [t, t+Δt], the electric vehicle status information at time t is updated (including the real-time charge status of the electric vehicle at time t and the charging status of the electric vehicle).

[0144] Step 4: Repeat step 2 in the next evaluation period until the exit condition is met and the operation ends.

[0145] 4. The response time margin (RTM) of an electric vehicle unit is defined as:

[0146] The response time margin characterizes the flexibility of the EV and is calculated as follows:

[0147]

[0148] Where RTM is the response time margin index of electric vehicle monomer, which represents the difference between the remaining parking time and the necessary charging time of electric vehicle monomer; S i (t) is the state of charge value of the i-th electric vehicle at time t, is the off-grid time of the i-th electric vehicle, is the expected state of charge of the ith electric vehicle when it is off-grid, S i (t) is the charge state of the ith electric vehicle at time t, Q i is the battery capacity of the i-th electric vehicle, is the SOC of the i-th electric vehicle when it joins the grid, is the time when the i-th electric car joins the grid.

[0149] RTM represents the difference between the remaining parking time and the necessary charging time. The larger the RTM, the greater the controllable flexibility of the electric vehicle. A large RTM value for an electric vehicle indicates that the charging demand is not urgent, and its discharge should be given priority. A small RTM value indicates that it is about to travel, and its charging should be given priority.

[0150] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0151] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0153] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A virtual power plant power control method based on electric vehicle response priority sequence, characterized in that: include: Acquire virtual power plant data, the virtual power plant data including basic information of electric vehicles, expected vehicle use time of users, minimum state of charge of electric vehicles to meet user travel needs, electric vehicle access time and initial state of charge information of electric vehicles; determine the power target value and response time period of electric vehicle clusters participating in the response based on the total power of the virtual power plant participating in the demand response; Conduct personalized modeling based on the historical charging and discharging data of electric vehicles to obtain the charging and discharging curve of electric vehicle monomers; The response time period is divided into multiple time intervals of equal length, and the response capability of the electric vehicle monomer is calculated according to the constraint conditions and the charge and discharge curve of the electric vehicle monomer; According to the electric vehicle cluster aggregation response capability and the power target value of the electric vehicle cluster participating in the response, the power target value of the electric vehicle cluster in each time interval is set; According to the minimum state of charge of electric vehicles that can meet the travel needs of users, the response time margin index RTM of electric vehicles is calculated; according to RTM, the current state of charge of electric vehicles and the power target value of the electric vehicle cluster in a single time interval, the response priority sequence of electric vehicles is established; Starting from the current time interval, the electric vehicle response priority sequence is updated cyclically and iteratively at the beginning of each time interval, and the power target value of each single electric vehicle is allocated and sent to the corresponding charging pile for execution until the response time period ends.

2. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 1 is characterized in that: According to the historical charging and discharging data of electric vehicles, personalized modeling is performed to obtain the charging and discharging curve of electric vehicle monomers, including: the current calculation formula of the electric vehicle battery is: In the formula, The current value required at time t to respond to the charge and discharge curve of the electric vehicle monomer n times, n-1 represents the number of times the electric vehicle battery charge and discharge has responded; Obtaining the state of charge of an electric vehicle cell when it is being charged based on the current value; Based on the initial state of charge information of the electric vehicle and the real-time state of charge of the electric vehicle during charging, a charge and discharge curve of the electric vehicle monomer is established; In the electric vehicle single-cell charge and discharge curve, according to the minimum state of charge of the electric vehicle to meet the user's travel needs and the maximum state of charge of the electric vehicle to meet the user's travel needs, the lower boundary line of the real-time state of charge of the electric vehicle when charging and the upper boundary line of the real-time state of charge of the electric vehicle when charging are constructed. The upper boundary line and the lower boundary line of the real-time state of charge of the electric vehicle when charging are the feasible domain of charging and discharging of the electric vehicle. The horizontal axis is the charging time, and the vertical axis is the state of charge of the electric vehicle when charging. S min is the minimum state of charge value of the electric vehicle, S e is the minimum state of charge of electric vehicles to meet the travel needs of users when off-grid, S s It is the initial state of charge information of the electric vehicle; When S s ≤S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging until the state of charge of the electric vehicle monomer reaches S min ; When S s >S min When the electric vehicle is connected to the grid and operates at rated power P e Start charging until the real-time state of charge of the electric vehicle reaches [S e ,S max ].

3. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 2 is characterized in that: The constraints include: The charging power or discharging power of electric vehicles needs to meet the following requirements: P(t)=m c (t)P c η c -m d (t)P d / η d , Where: P(t) is the real-time charging power or discharging power of the electric vehicle, P c is the real-time charging power of the electric vehicle, P d is the real-time discharge power of the electric vehicle, η c is the charging efficiency of electric vehicles, η d is the discharge efficiency of electric vehicles; m c (t) is the online charging status of the electric vehicle, m c (t) = 1 means it is in charging state, m c (t) = 0 means it is in the non-charging state; m d (t) is the discharge state of the electric vehicle, m d (t) = 1 means it is in the discharge state, m d (t) = 0 means it is in the non-discharging state, m c (t)+m d (t)≤1; When charging an electric vehicle, the following conditions must be met: E min ≤E(t)≤E max , Where S(t) is the real-time state of charge of the electric vehicle when charging, t s The starting moment of charging the electric vehicle, B e is the battery capacity of the electric vehicle, E(t) is the real-time power of the electric vehicle, and E s is the initial charge of the electric vehicle, E max is the maximum amount of electricity that an electric car can hold, E min is the minimum amount of electricity that an electric vehicle can hold, is the maximum charging power of the electric vehicle, P c is the actual charging power of the electric vehicle, is the maximum discharge power of the electric vehicle, P d is the actual discharge power of the electric vehicle; the upper and lower boundaries of the power of the electric vehicle when charging a single unit must meet the following requirements: E up (t)=min(E(t),E max ),t∈(t s ,t d ) E dn (t)=max(E(t),E min ) In the formula, E up (t) is the maximum amount of electricity when the electric vehicle is charged at time t, E dn (t) is the minimum power value of the electric vehicle when charging at time t, E e The initial charge when charging an electric vehicle, t s and t d is a constant, t s <t d , t d The moment to stop charging your electric car.

4. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 3 is characterized in that: The response time period is divided into multiple time intervals of equal length, and the response capability of electric vehicle monomers is calculated according to the constraint conditions and the charge and discharge curves of electric vehicle monomers, including: Based on the feasible domain of electric vehicle charging and discharging, the single-cell response capability of electric vehicles is calculated: The response time period [t1, t2] is divided into m time periods of length Δt, t1 and t2 are constants, t1+Δt≤t2, m=(t2-t1) / Δt, and the charging power of the electric vehicle remains unchanged within Δt, then: Where, E(t) is the real-time power of the electric vehicle, E s is the initial power of the electric vehicle when it is charged, P(k) is the current charging power of the electric vehicle, v(k) indicates whether the electric vehicle is charged online in the kth time period, k∈[1,m], v(k)=1 indicates online charging, and v(k)=0 indicates offline not charging; The maximum charging power that can be increased or reduced for an electric vehicle unit is: Where P + (k) represents the maximum charging power that can be increased for an electric vehicle unit, P - (k) represents the maximum reducible charging power of an electric vehicle; To consider the maximum power range that can be increased by power constraints, E up (k+1)-E(k) is the maximum chargeable power of the electric vehicle in the kth period, (E up (k+1)-E(k)) / Δt+P(k) is the impact of power constraints reflected by the rechargeable potential of electric vehicle monomers under current working conditions, E up (k+1) is the upper limit of the electric vehicle's battery capacity at the beginning of the k+1th period, is the maximum discharge power of the electric vehicle, E(k) is the electric vehicle power at the beginning of the kth period, and E dn (k+1) is the lower limit of the electric vehicle's single power at the beginning of the k+1th period; The maximum charging power that can be increased or reduced by an electric vehicle cluster is: Where: The maximum charging power that can be increased for an electric vehicle cluster. is the maximum charging power that can be reduced by the electric vehicle cluster, N is the total number of electric vehicle monomers in the electric vehicle cluster, i∈[1,N]; P + (i,k) is the maximum power that can be increased by the i-th electric vehicle unit in the k-th period, P - (i,k) is the maximum power that can be reduced for the i-th electric vehicle unit in the k-th time period.

5. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 4 is characterized in that: Calculate the RTM index of the electric vehicle monomer response time margin: Where RTM is the response time margin index of electric vehicle monomer, which represents the difference between the remaining parking time and the necessary charging time of electric vehicle monomer; S i (t) is the state of charge value of the i-th electric vehicle at time t, is the off-grid time of the i-th electric vehicle, is the expected state of charge of the ith electric vehicle when it is off-grid, S i (t) is the charge state of the ith electric vehicle at time t, Q i is the battery capacity of the i-th electric vehicle, is the SOC of the i-th electric vehicle when it joins the grid, is the time when the i-th electric car joins the grid.

6. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 5 is characterized in that: According to the RTM, the current state of charge of the electric vehicle and the power target value of the electric vehicle cluster in a single time interval, an electric vehicle response priority sequence is established, including: Step 1: Collect the state of charge of electric vehicles at time t1 and calculate the initial electric vehicle cluster aggregation response capability; Step 2: Within the EV cluster aggregate response capability, set the EV cluster power target value P within the response time period [t, t+Δt] S , according to the dispatching instructions, filter and regulate electric vehicles, and obtain the electric vehicle priority queue response system dispatch: When the dispatch instruction requires the electric vehicle cluster to increase the response power, the corresponding electric vehicles are sequentially stopped from discharging in descending order according to the RTM values. When the RTM values ​​are the same, the electric vehicles with a smaller state of charge are given priority to stop discharging. When all electric vehicles stop discharging and the need for the electric vehicle cluster to increase the response power is still not met, the corresponding electric vehicles are sequentially charged in ascending order according to the RTM values. When the RTM values ​​are the same, the electric vehicles with a smaller state of charge are given priority to start charging. When the dispatch instruction requires the electric vehicle cluster to reduce the response power, the corresponding electric vehicles are stopped charging in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicles with a large state of charge are stopped charging first. When all electric vehicles stop charging and still cannot meet the electric vehicle cluster's response power reduction demand, the corresponding electric vehicles are started to discharge in order from large to small RTM values. When the RTM values ​​are the same, the electric vehicles with a large state of charge are started to discharge first. Step 3: According to the generated electric vehicle priority queue response system scheduling, check whether the response power P of the electric vehicle reaches the power target value P S , if the power target value P is reached S Then the operation is terminated, otherwise the real-time state of charge of the electric vehicle and the charging state of the electric vehicle at time t are updated according to the electric vehicle priority queue response system scheduling within [t, t+Δt]; Step 4: Increase the value of t by Δt and run step 2.

7. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 1 is characterized in that: Access virtual power plant data, including: Users register on the virtual power plant management and control system platform and enter basic information about electric vehicles; The user enters the user's expected vehicle usage time and the minimum charge state of the electric vehicle that meets the user's travel needs on the mobile client; the basic information of the electric vehicle includes the production time of the electric vehicle, the battery capacity of the electric vehicle and the model of the electric vehicle.

8. The virtual power plant power control method based on electric vehicle response priority sequence according to claim 6 is characterized in that: Allocate and issue the power target value P of each electric vehicle S Execute the corresponding charging pile until the response time period ends, including: Allocate and sequentially send the power target value of each electric vehicle to the corresponding charging pile for execution; (1) If the power target value P S If it is greater than the P(t) of the current electric vehicle monomer, the electric vehicle monomers discharging to the grid through the charging pile will be issued a stop discharge command one by one according to the RTM values ​​of the electric vehicle monomers from large to small, and the real-time charging power of the electric vehicle monomers will be 0; If there is no electric vehicle unit in the electric vehicle cluster that is in a discharging state and the current electric vehicle unit's P(t) <P S If the value of the RTM value of the electric vehicle monomer is established, charging instructions are issued to the electric vehicle monomers one by one in ascending order, and the real-time charging power of the electric vehicle monomer is the maximum charging power of the monomer. Electric vehicle monomers with the same RTM value are accepted and executed in order of the state of charge from the smallest to the largest; After the current electric vehicle monomer successfully starts charging, check the P(t) of the current electric vehicle monomer <P S Is it established? If so, continue to issue the next electric vehicle single power target value; If the power target value P S If the power is less than the real-time power P(t), the stop charging command is issued to each electric vehicle monomer in descending order according to the RTM value of the electric vehicle monomer, and the real-time charging power of the electric vehicle monomer is 0; When there is no electric vehicle in the charging state in the electric vehicle cluster and P(t)>P S If the RTM value of the electric vehicle is established, the electric vehicle monomers connected to the charging piles in the electric vehicle cluster are issued discharge instructions one by one in descending order. The real-time charging power of the electric vehicle monomer is the maximum discharge power of the monomer. Electric vehicle monomers with the same RTM value receive and execute discharge instructions in descending order according to the charge state of the electric vehicle monomers; After each discharge instruction is issued and executed successfully, it is determined that the electric vehicle cluster P(t)>P S Is it established? If so, continue to issue the next single power target value of the electric vehicle.

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