CN112590601B - V2G charging station system based on edge computing platform - Google Patents

Abstract

The invention discloses a new V2G charging station system based on an edge computing platform and a charging method thereof. The intelligent recommended charging solution is an edge computing platform that can achieve maximum charging profit for users who stay for a long time through the scheduling optimization of the station.

Description

V2G charging station system based on edge computing platform

technical field

The invention relates to the technical field of electric vehicle charging, in particular to a V2G charging station system based on an edge computing platform.

Background technique

The environmental protection and economic benefits of electric vehicles are obvious, but as the proportion of electric vehicles in the market gradually increases, the impact of their access to the power grid cannot be ignored. The charging load of electric vehicles is very different from other traditional power loads in the power system. In the absence of a reasonable scheduling strategy, especially in the gathering high-power charging and peak charging scenarios, the random charging behavior of users is very likely to cause grid damage. "Peak-to-peak" even generates new peaks in electricity consumption, increasing the burden on the power system and may directly lead to grid paralysis.

At the same time, the charging behavior of grid electricity consumption peak also makes charging users bear higher charging expenses, thereby reducing the attractiveness of charging stations and taking on the risk of grid curtailment. A large number of studies and survey results show that about 90% of private vehicles have an average daily travel time of only about 1 hour, which means that most vehicles are idle for a long time. Therefore, in the field of intelligent transportation, Vehicle-to-Grid (V2G) can reasonably standardize the charging and feeding behavior of electric vehicles through the V2G two-way interaction between the power grid and electric vehicle users, which can effectively reduce its possible impact on the power grid. The various negative effects of the grid can be used to “cut peaks and fill valleys” for the power grid; it can also give full play to the energy storage characteristics of electric vehicle on-board batteries, and select access to charge and store energy during low-load and low-price periods of the grid, and vice versa. . Select to connect reverse feed during high electricity price period, which can stabilize or reduce the charging expenses of users while ensuring the quality of high-power fast charging service at the station, and effectively reduce operating costs and pressures.

Existing V2G charging stations have the following disadvantages:

1. The existing V2G charging station system is inseparable from the load prediction results of the power grid system in the same station area. The energy management and dispatching system of the charging station undertakes more power grid dispatching functions, resulting in system redundancy and complexity.

2. Existing V2G charging stations rarely comprehensively consider how to balance grid stability, station operating profits and user charging costs for dispatch management.

3. High-power DC charging piles will become the absolute protagonists of public/commercial charging services, but pure high-power DC charging piles will exacerbate the peak power consumption caused by cluster charging and peak charging, limiting their rapid and large-scale development.

4. The peak and valley period is a relatively fixed power grid. A simple V2G charging station can reasonably arrange the electric vehicle feed to make the "peak shaving" effect obvious; but the battery capacity of the electric vehicle is limited, and the pure V2G charging station can charge in an orderly manner. The effect of "filling the valley" is no different from the usual medium and low power charging stations.

SUMMARY OF THE INVENTION

In order to overcome the above shortcomings, the purpose of the present invention is to provide a V2G charging field based on an edge computing platform that can not only intelligently recommend a charging scheme for users, but also strive for maximum charging profit for users who stay for a long time through the scheduling optimization of the field station. station system.

In order to achieve the above purpose, the technical solution adopted in the present invention is: a V2G charging station system based on an edge computing platform, characterized in that:

Charging scheduling management control and operation system: It is composed of a charging scheduling management control platform and a charging operation platform. The charging scheduling management control platform receives the electrical status data of the intelligent terminals in the grid station area, the user demand information of the charging operation platform, and the pile group scheduling control. The status information and control strategy information of the system's pile group operation and the power grid scheduling requirement information of the upper-level power grid dispatching control system, formulate the operation strategy and send it to the lower-level pile group as an execution reference, and the charging operation platform receives the charging order information and charging discount/subsidy behavior information Calculate charging discounts/subsidies, perform charging fee settlement and notify users to perform settlement, receive charging demand information from the user's charging application and send it to the overall charging scheduling management and control platform, receive charging plan information from the charging scheduling management and control platform, and send it to the user's charging application For users to know, the charging scheme information includes the following steps:

1) The user manually enters or presets the target SOC value of the current charging through the user charging application terminal, which is recorded as SOC ₁ ;

2) Estimate the charging time of the three charging schemes, namely: ① Ordinary charging, that is, the electric vehicle is charged immediately after starting the charging until the charging service stops because the power battery is full; ② Off-peak charging, that is, based on ordinary charging, if the charging period is After the peak electricity price of the grid, the charging will be temporarily stopped until the charging service is stopped because the power battery is full during the off-peak electricity price period; ③Economic charging, that is, during the charging period, the electric vehicle first feeds power to the grid to the set allowable discharge depth during the peak electricity price period , and recharge to the user's target SOC;

3) Estimate the amount of charging discount for the three charging schemes;

4) Push the estimation results of the three charging schemes to the user's charging application;

5) The user selects the charging scheme;

6) If the user participates in the V2G response, the energy management scheduling method of the V2G charging station is invoked to generate a charging plan; if the user does not participate in the V2G response, the charging plan is generated according to the charging plan selected by the user;

7) Execute the charging plan according to the scheduling control quantity P _ev-opt(i,j) ;

8) Each corresponding charging device responds to the charging plan instruction;

9) After a certain interval of time after the response of the previous step, if the charging of the electric vehicle connected to the charging device is completed, end the charging function of the corresponding device and submit it to the user for settlement. one step;

10) Judging whether the charging plan parameters in the field station have changed, when there is a change, return to step 6)-8); when there is no change, continue to execute the current charging plan, and the charging plan parameters include the user changing the departure time, Emergency stop of charging and grid scheduling commands for some reason.

Further, it also includes a power grid dispatching control system: receiving regional charging operation information of the overall charging dispatching management and control platform, and sending collaborative dispatching information, where the collaborative dispatching information is demand response, station load prediction, dispatching response strategy, and the like.

Further, it also includes a pile group scheduling control system: uploading the status information and control strategy information of the pile group operation to the upper-level charging scheduling management and control general platform, receiving the electric vehicle charging and discharging operation information of the lower-level charging pile group system, and combining with the upper-level charging scheduling management Control the requirements issued by the main platform, formulate operation strategies and send them to each subordinate charging pile for execution.

Further, it also includes a charging pile group system: collects the charging and discharging operation information of electric vehicles, and sends it to the edge IoT agent computing platform of the pile group dispatching control system and the charging operation platform of the charging dispatching management control and operation system, and accepts and executes the superior. The charging and discharging instructions of the charging pile connected to the electric vehicle issued by the system.

Further, the range of the grid platform area is a single distribution grid area with voltage levels of 110kV, 10kV and 380V.

Further, in step 2), the estimated charging time of the three charging schemes 1) Equivalent discharge with constant rated power, that is, the equivalent discharge amount from the current SOC of the electric vehicle to the allowable depth of discharge, and the shortest time t _{chp0 required} :

in,

SOC ₀ is the SOC value when the electric vehicle starts to charge;

D ₀ is the allowable depth of discharge for electric vehicles;

P _V2G-dch is the rated discharge power of the V2G charging pile;

It should be noted that the rated charging/discharging power of the electric vehicle should not be less than the rated charging/discharging power of the charging pile;

2) The whole process of charging the electric vehicle to SOC ₁ consists of two stages, in which there is a critical value SOC _vb of the SOC related to the battery voltage of the electric vehicle;

a) If SOC ₁ ≤ SOC _vb , charge with constant power throughout the whole process:

The normal charging process duration t _chp1 is:

The process duration t _chp2 of deep charging is:

b) If SOC ₁ >SOC _vb , charge with constant power when SOC≤SOC _vb , and charge with constant voltage when SOC>SOC _vb :

The normal charging process duration t _chp3 is:

The duration of the deep charging process t _chp4 is:

in,

P _V2G-ch is the rated charging power of the V2G charging pile;

P _V2G-ch(t) is a function of the charging power of the V2G charging pile in the constant voltage charging state, which changes with time;

3) Estimated value of ordinary charging time:

If SOC ₁ ≤SOC _vb , then t _ch1 =t _chp1

If SOC ₁ >SOC _vb , then t _ch1 =t _chp3

4) Estimated off-peak charging time:

If T ₀ +t _ch1 ≤T _pop , then t _ch2 =t _ch1

If T ₀ +t _ch1 >T _pop , then t _ch2 =t _ch1 +t _pop

in,

t _pop is the duration of the grid peak electricity price that is closest to the charging start time T ₀ and starts at time T _pop ;

5) Estimated value of economical charging time:

a) When t _chp0 >t _pop , that is, when the electric vehicle cannot be discharged to D ₀ at a constant rated power during the equivalent peak electricity price, there is an estimated value A of the economical charging time

If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp1 +(1+SC _dch-ch )t _pop

If SOC ₁ >SOC _vb , then t _ch3 =t _chp3 +(1+SC _dch-ch )t _pop

b) When t _{chp0 ≤} t _pop , that is, when the electric vehicle can be discharged to D ₀ with a constant rated power during the equivalent peak electricity price, there is an estimated value B of the economical charging time

If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp2 +t _pop

If SOC ₁ >SOC _vb , then t _ch3 =t _chp4 +t _pop

in,

SC _dch-ch is the ratio of the rated discharge power to the rated charging power of the V2G charging pile.

Further, estimating the charging discount amount of the three charging schemes in step 3) includes the following steps: 1) The charging discount amount for ordinary charging and off-peak charging is 0

2) The charging discount for economical charging is υ*t _pop

3) Calculate the charging cost of the plan

a) Ordinary charging fee:

b) Off-peak charging fee:

c) Economic charging fee:

in,

P _r (j) the high-power charging electricity price of the electric vehicle in the j time window, and the charging electricity price is negative;

P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window;

T _ch1 =t _ch1 /Δt, T _ch2 =t _ch2 /Δt, T _pop =t _pop /Δt.

Further, in step 4), pushing the estimation results of the three charging schemes to the user charging application terminal includes the following steps: normal charging [t _ch1 , cst _ch1 ], off-peak charging [t _ch2 , cst _ch2 ] and economic charging [t ch1 , cst ch1 ] t _ch3 ,cst _ch3 ] are pushed to the user's charging application.

Further, the charging scheme selected by the user in step 5) includes the following steps:

1) If the ordinary charging scheme and the off-peak charging scheme are adopted, the user does not participate in the V2G response;

2) If the economical charging scheme is adopted, then:

a) When T ₀ +t _ch3 ≤T _s , temporarily judge that the user can participate in the V2G response;

b) When T ₀ +t _ch3 >T _s , temporarily judge that the user cannot participate in the V2G response;

3) Among them, the user can input the scheduled departure time at any time during the charging period, if the user inputs the scheduled departure time, set T _s as the user scheduled departure time; if the user does not input the scheduled departure time, set Set T _s as the estimated charging time of the scheme.

Further, the charging plan of the step 6) includes the following steps:

1) Establish a grid-side demand response model of the V2G charging station, where the grid-side demand response model includes:

a) The expected effect of the station participating in the grid-side demand response:

in,

N is the total number of electric vehicles;

g ₁ is the proportion of electric vehicles that can participate in the V2G response scheduling strategy;

N ₁ is its corresponding specific quantity;

g ₂ is the proportion of electric vehicles that do not participate in the V2G response scheduling strategy, g ₂ =1-g ₁ ;

N ₂ is its corresponding specific quantity;

P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window;

P _chs (j) is the expected V2G charging station load of the grid in the j time window;

b) The benefits of the station participating in the grid-side demand response:

in,

λ(P _DR ) represents the efficiency function of the V2G charging station to reduce the load peak-to-valley difference, and reflects the effect of the station on the grid-side demand response in the form of revenue;

P _r0 (j) is the reward price obtained by the V2G charging station in the j time window by reducing the load peak-to-valley difference, and the reward price is negative;

T is the number of time windows, T=24/Δt;

2) Operational revenue model of V2G charging station, the operational revenue model includes:

in,

P _r1 (j) is the electricity price for the charging station to purchase or sell electricity through the power grid in the j time window, the electricity purchase price is negative, and the electricity sales price is positive;

P _r2 (j) is the charging or discharging electricity price of the electric vehicle in the j time window, the charging electricity price is negative, and the discharging electricity price is positive;

P _ev (i,j) is the operating power of the i-th charging pile in the j time window, charging is positive and discharging is negative;

Δt represents a scheduling time window;

3) Comprehensive income model of V2G charging station, the comprehensive income model includes:

F _S =a ₀ f ₀ +a ₁ f ₁ ;

in,

a ₀ and a ₁ are the weighting factors of the demand response revenue of the site and the revenue of the V2G site, respectively, a ₀ +a ₁ =1;

4) Establish a V2G user benefit model, which includes:

a) The charging expenditure of the user's electric vehicle is:

b) The psychological subsidy f _C1 for depreciation of the user's electric vehicle power battery due to non-travel discharge behavior is:

When P _ev (i,j)>0, f _C1 =0;

When P _ev (i,j)<0,

in,

β is the depreciation subsidy price coefficient for battery discharge, which is negative;

c) The cost of comprehensively obtaining the charging/discharging behavior of V2G users is:

F _C =f _C0 +f _C1 ;

5) V2G charging station energy management scheduling optimization objectives, the scheduling optimization objectives include:

F∈max F _S ∩min F _C ;

When the dual goals of maximizing V2G charging station revenue and minimizing user charging expenditures can be met at the same time, the charging/discharging power P _ev-opt(i,j) of the i-th electric vehicle j time window is the scheduling control quantity, The energy management scheduling optimization objective can be transformed into a single objective with respect to satisfying the minimum of the binary variables F _S and F _C :

min _F =(-FS , _FC ) ^T .

Further, the type of charging piles to which the pile group scheduling control system belongs is any one or more of AC charging piles, DC charging piles, V2G charging piles, charging piles, charging bows, and automatic charging equipment.

Further, the scheduling management control system of the charging field station serves as the scheduling management controller of the charging field station or the regional charging field station, and has jurisdiction over a plurality of edge IoT proxy computing platforms.

Further, the dispatching management control system of the charging station is composed of a plurality of charging pile group systems, which form a plurality of sub-pile group dispatching control systems through respective edge IoT proxy computing platforms, and are uniformly connected to the dispatching management control system of the charging station. Take control.

Further, the form of the user charging application terminal includes a mobile phone APP, a charging pile touch screen, voice recognition software and hardware, and smart home equipment, which are directly or indirectly connected to the charging operation platform through physical communication means to realize data interaction. The means include Ethernet, 3G\4G\5G wireless communication, and local area network.

Compared with the prior art, the present invention has the following beneficial effects:

1. The new V2G station charging scheduling management and control system has a flexible structure. It can rely on the charging scheduling management and control main platform or the edge IoT agent computing platform to manage and control the charging scheduling of the station according to different needs.

2. The new V2G charging start control and energy scheduling control method, this method makes up for the current V2G charging energy scheduling method that must first ask for charging behavior parameters, which leads to the complexity of charging start, and adopts the method of recommending intelligent solutions to improve user-friendliness .

3. The new V2G charging station energy scheduling method takes into account the “peak shaving and valley filling” demand of the power grid, the operating income of the charging station and the rights and interests of V2G charging users, and relies on the rapid response of edge computing to improve the reliability and reliability of station scheduling management. The superimposed computing power reduces the delay of the dispatching management of the field station.

4. The integrated charging station not only satisfies V2G users to feed power to the grid to earn feedback, but also can obtain charging discounts or subsidies by providing electric energy to high-power charging equipment at the same station, combining V2G's "peak shaving" function with The "valley filling" function of high-power charging complements each other, effectively stabilizing the load of the power grid.

Description of drawings

1 is a schematic diagram of a charging scheduling management control system;

Fig. 2 is the flow chart of start-up control and energy dispatch control;

Fig. 3 is a flow chart of the charging duration for estimating the charging scheme in formulating the charging scheme;

Fig. 4 is a flowchart showing the charging cost estimation of the charging scheme according to the charging duration in formulating the charging scheme;

5 is a schematic structural diagram of an electrical system;

FIG. 6 is a schematic structural diagram of an electrical system.

In the picture:

1- Charging pile group system; 2- Pile group dispatching control system; 3- Charging dispatch management control and operation system; 4- Power grid dispatching control system; 5- High-power charging equipment; 6- V2G charging equipment; Busbar; 8-Sub-busbar of access device 7.

Detailed ways

The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, and the protection scope of the present invention can be more clearly defined.

Referring to Figure 1, the new V2G field station charging management and control system based on the edge computing platform consists of four levels of systems:

Charging pile group system 1: Collect the charging and discharging operation information of electric vehicles, such as the charging and discharging status of electric vehicles, the user's expected charging amount and the expected stay time, etc., and send it to the edge IoT proxy computing platform and charging scheduling of the pile group scheduling control system 2 at the same time The charging operation platform of the management control and operation system 3; accepts and executes the charging and discharging instructions of the charging pile connected to the electric vehicle issued by the superior system;

Pile group scheduling control system 2: Upload the status information and control strategy information of the pile group operation to the upper-level charging scheduling management control platform; According to the requirements issued, formulate an operation strategy and send it to each subordinate charging pile for implementation;

Charging scheduling management control and operation system 3: It is composed of two physically separated subsystems, the charging scheduling management control platform and the charging operation platform. The subsystems realize information exchange through wired or wireless networks. Among them, the charging dispatching management and control general platform receives the electrical status data of the intelligent terminals in the grid station area, the user demand information of the charging operation platform, the status information and control strategy information of the pile group operation of the pile group dispatching control system, and the upper-level power grid dispatching control system. Power grid scheduling requirements information, formulate operation strategies and send them to lower-level pile groups as execution reference; the charging operation platform receives charging order information and charging discount/subsidy behavior information to calculate charging discounts/subsidies, and performs charging fee settlement to notify users to execute settlement; receive user charging applications The charging demand information of the terminal is sent to the charging scheduling management and control general platform; the charging scheme information of the charging scheduling management and control general platform is received, and sent to the user charging application terminal for the user to know;

Grid dispatching control system 4: Receive regional charging operation information of the overall charging dispatching management and control platform, and send coordinated dispatching information, such as demand response, load forecasting, dispatching response strategy, etc.

Further, the grid platform area ranges from a single distribution grid area of 110kV, 10kV and 380V voltage classes.

Further, the types of charging piles to which the pile group scheduling control system belongs can be AC charging piles, DC charging piles, V2G charging piles, charging piles, charging bows, automatic charging equipment, etc., or can be various types of charging piles. mix.

Further, the overall charging scheduling management and control platform is usually used as the scheduling management controller of the charging station or the regional charging station, and has jurisdiction over multiple edge IoT proxy computing platforms (ie, the pile group scheduling control system).

Scalable, the dispatching management and control system of a charging station can be composed of a plurality of different charging pile group systems constructed for various purposes, and multiple sub-pile group dispatching control systems can be formed through their respective edge IoT proxy computing platforms. Access to the charging scheduling management and control general platform to accept control. The scheduling management and control system of a regional charging station can only connect multiple charging devices of multiple types to the edge IoT proxy computing platform to accept the control of the corresponding station, and then the overall charging scheduling management and control platform can manage and control the access. charging station.

Further, the user's charging application can be in the form of mobile APP, charging pile touch screen, voice recognition software and hardware, smart home equipment, etc., directly or indirectly through physical communication means such as Ethernet, 3G\4G\5G wireless communication, local area network, etc. Connect to the charging operation platform to realize data exchange.

Further, the edge IoT proxy computing platform (ie the pile group scheduling control system) provides a new method of V2G charging start control and energy scheduling control, which makes up for the current V2G charging energy scheduling method that must first request charging behavior parameters. This leads to the complexity of charging and starting, and the user-friendliness is improved by recommending an intelligent solution;

1) The user manually enters or presets the target SOC value of the current charging through the user charging application terminal, which is recorded as SOC ₁ ;

2) Estimating the charging time of the three charging schemes, as shown in Figure 2, the proposed three charging schemes based on V2G are: ① Ordinary charging, that is, the electric vehicle is charged immediately after starting the charging until the power battery is fully charged. Service stop; ② Off-peak charging, that is, based on ordinary charging, temporarily stop charging if it experiences the peak electricity price of the grid during the charging period, until the charging service is stopped due to the full power battery during the off-peak electricity price period; ③ Economic charging, that is, electric charging during charging During the peak electricity price period, the car first feeds power to the grid to the set allowable depth of discharge, and then charges to the user's target SOC;

2-1) Equivalent discharge with constant rated power, that is, the equivalent discharge amount from the current SOC of the electric vehicle to the allowable depth of discharge, and the shortest time t _{chp0 required} :

in,

SOC ₀ is the SOC value when the electric vehicle starts to charge;

D ₀ is the allowable depth of discharge for electric vehicles;

P _V2G-dch is the rated discharge power of the V2G charging pile;

It should be noted that the rated charging/discharging power of the electric vehicle should not be less than the rated charging/discharging power of the charging pile;

2-2) The whole process of charging the electric vehicle to SOC ₁ consists of two stages, in which there is a critical value SOC _vb of the SOC related to the battery voltage of the electric vehicle;

a) If SOC ₁ ≤ SOC _vb , charge with constant power throughout the whole process:

The normal charging process duration t _chp1 is:

The process duration t _chp2 of deep charging is:

b) If SOC ₁ >SOC _vb , charge with constant power when SOC≤SOC _vb , and charge with constant voltage when SOC>SOC _vb :

The normal charging process duration t _chp3 is:

The duration of the deep charging process t _chp4 is:

in,

P _V2G-ch is the rated charging power of the V2G charging pile;

P _V2G-ch (t) is a function of the charging power of the V2G charging pile in the constant voltage charging state as a function of time;

2-3) Estimated value of ordinary charging time:

If SOC ₁ ≤SOC _vb , then t _ch1 =t _chp1

If SOC ₁ >SOC _vb , then t _ch1 =t _chp3

2-4) Estimated value of off-peak charging time:

If T ₀ +t _ch1 ≤T _pop , then t _ch2 =t _ch1

If T ₀ +t _ch1 >T _pop , then t _ch2 =t _ch1 +t _pop

in,

t _pop is the duration of the grid peak electricity price that is closest to the charging start time T ₀ and starts at time T _pop ;

2-5) Estimated value of economical charging time:

a) When t _chp0 >t _pop , that is, when the electric vehicle cannot be discharged to D ₀ at a constant rated power during the equivalent peak electricity price, there is an estimated value A of the economical charging time

If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp1 +(1+SC _dch-ch )t _pop

If SOC ₁ >SOC _vb , then t _ch3 =t _chp3 +(1+SC _dch-ch )t _pop

b) When t _{chp0 ≤} t _pop , that is, when the electric vehicle can be discharged to D ₀ with a constant rated power during the equivalent peak electricity price, there is an estimated value B of the economical charging time

If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp2 +t _pop

If SOC ₁ >SOC _vb , then t _ch3 =t _chp4 +t _pop

in,

SC _dch-ch is the ratio of the rated discharge power to the rated charging power of the V2G charging pile;

3) Referring to Figure 3, estimate the amount of charging discount for the three charging schemes,

3-1) The charging discount for normal charging and off-peak charging is 0

3-2) The charging discount for economical charging is υ*t _pop

3-3) Calculate the charging cost of the plan

a) Ordinary charging fee:

b) Off-peak charging fee:

c) Economic charging fee:

in,

P _r (j) the high-power charging electricity price of the electric vehicle in the j time window, and the charging electricity price is negative;

P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window;

T ^ch1 =t _ch1 /Δt, T _ch2 =t _ch2 /Δt, T _pop =t _pop /Δt;

4) Push the estimation results of the three charging schemes: ordinary charging [t _ch1 , cst _ch1 ], off-peak charging [t _ch2 , cst _ch2 ] and economical charging [t _ch3 , cst _ch3 ] to the user charging application terminal;

5) The user selects the charging scheme,

5-1) If the ordinary charging scheme and the off-peak charging scheme are adopted, the user does not participate in the V2G response;

5-2) If the economical charging scheme is adopted, then:

a) When T ₀ +t _ch3 ≤T _s , temporarily judge that the user can participate in the V2G response;

b) When T ₀ +t _ch3 >T _s , temporarily judge that the user cannot participate in the V2G response;

5-3) Among them, the user can input the scheduled departure time at any time during the charging period. If the user inputs the scheduled departure time, set T _s as the user's scheduled departure time; if the user does not input the scheduled departure time, Then set T _s as the estimated charging time of the scheme;

6) If the user participates in the V2G response, the energy management scheduling method of the V2G charging station is invoked to generate a charging plan; if the user does not participate in the V2G response, the charging plan is generated according to the charging plan selected by the user;

Among them, the carrier platform that invokes the energy management scheduling method and generates the charging plan depends on whether the role of the scheduling management control system is the edge IoT proxy computing platform or the overall charging scheduling management and control platform;

Further, referring to Figure 4, a charging energy scheduling method is provided that takes into account the "peak shaving and valley filling" of the power grid, the operating income of the station and the rights and interests of V2G users, specifically:

6-1) Establish a grid-side demand response model for V2G charging stations, specifically:

a) The expected effect of the station participating in the grid-side demand response:

in,

N is the total number of electric vehicles;

g ₁ is the proportion of electric vehicles that can participate in the V2G response scheduling strategy;

N ₁ is its corresponding specific quantity;

g ₂ is the proportion of electric vehicles that do not participate in the V2G response scheduling strategy, g ₂ =1-g ₁ ;

N ₂ is its corresponding specific quantity;

P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window;

P _chs (j) is the expected V2G charging station load of the grid in the j time window;

b) The benefits of the station participating in the grid-side demand response:

in,

λ(PDR) represents the efficiency function of the V2G charging station to reduce the load peak-to-valley difference, and reflects the effect of the station on the grid-side demand response in the form of revenue;

P _r0 is the reward price obtained by the V2G charging station in the j time window by reducing the load peak-to-valley difference, and the reward price is negative;

T is the number of time windows, take T=24/Δt;

6-2) Operational revenue model of V2G charging station, specifically:

in,

P _r1 (j) is the electricity price for the charging station to purchase or sell electricity through the power grid in the j time window, the electricity purchase price is negative, and the electricity sales price is positive;

P _r2 (j) is the charging or discharging electricity price of the electric vehicle in the j time window, the charging electricity price is negative, and the discharging electricity price is positive;

P _ev (i,j) is the operating power of the i-th charging pile in the j time window, charging is positive and discharging is negative;

Δt represents a scheduling time window;

6-3) Comprehensive income model of V2G charging station, specifically:

F _S =a ₀ f ₀ +a ₁ f ₁ ;

in,

a ₀ and a ₁ are the weighting factors of the demand response revenue of the site and the revenue of the V2G site, respectively, a ₀ +a ₁ =1;

6-4) Establish a V2G user benefit model, specifically:

a) The charging expenditure of the user's electric vehicle is:

b) The psychological subsidy f _C1 for depreciation of the user's electric vehicle power battery due to non-travel discharge behavior is:

When P _ev (i,j)>0, f _C1 =0;

When P _ev (i,j)<0,

in,

β is the depreciation subsidy price coefficient of battery discharge, which is a negative value;

c) The cost of comprehensively obtaining the charging/discharging behavior of V2G users is:

F _C =f _C0 +f _C1 ;

6-5) Optimization objectives of energy management scheduling of V2G charging stations, specifically:

F∈max F _S ∩min F _C ;

That is, when the dual goals of maximizing the revenue of the V2G charging station and minimizing the user's charging expenditure can be satisfied at the same time, the charging/discharging power P _ev-opt (i,j) of the i-th electric vehicle j time window is the scheduling control quantity. , the energy management scheduling optimization objective can be transformed into a single objective with respect to satisfying the minimum value of the binary variables FS and FC:

min F=(-F _S , F _C ) ^T ;

The specific solution and calculation method of the variable of the target minimum value and its steps are well known to those skilled in the art, and the present invention will not repeat them;

7) Execute the charging plan according to the scheduling control quantity P _ev-opt (i, j);

8) Each corresponding charging device responds to the charging plan instruction;

9) After a certain interval (for example, 15 minutes) after the response of the previous step, if the charging of the electric vehicle connected to the charging device is completed, the charging function of the corresponding device will be terminated and the user will be submitted for settlement; if it is still charging, the charging plan will not be considered. completed, and proceed to the next step;

10) Determine whether the charging plan parameters in the station have changed, if so, return to step 6)-8); if not, continue to execute the current charging plan, wherein the charging plan parameters include but are not limited to changes by the user Departure time, emergency stop charging for any reason, grid dispatching orders, etc.

Based on the above-mentioned V2G charging station, the present invention can also be applied to a V2G-based comprehensive high-power charging station. Cars feed power to the grid via V2G to earn feedback, and during peak load and peak electricity price periods, provide power to high-power charging equipment to reduce the overall operating costs of the station;

This embodiment provides two types of typical electrical system structures suitable for such integrated charging stations;

Referring to Figure 5, all V2G equipment and high-power charging equipment in the station are connected into a bus in parallel, and the rated current carrying capacity of the bus should not be less than the total rated current carrying capacity of all charging equipment, that is, I _V2G + I _FC ≤ I _BUS ;

Referring to Figure 6, several V2G devices and a high-power charging device are connected in parallel to a branch bus I-1, and several of the branches similar to the branch bus I-1 are connected to a plurality of V2G devices and a high-power charging device. The branch busbars I-2, ..., IK are all connected in parallel to a main busbar I, and the rated current carrying capacity of each branch busbar should not be less than the rated charging current of the high-power charging equipment connected to it, that is, I _FC(k) ≤ I _Ik ;

Further, the charging energy scheduling method of the comprehensive charging station is as follows:

1) Establish a grid-side demand response model for integrated charging stations, specifically:

in,

N _V2G is the total number of electric vehicles using V2G charging equipment, namely N _V2G =N ₁ +N ₂ ;

g ₁ is the proportion of electric vehicles that can participate in the V2G response scheduling strategy;

N ₁ is its corresponding specific quantity;

g ₂ is the proportion of electric vehicles that do not participate in the V2G response scheduling strategy, that is, g ₂ =1-g ₁ ;

N ₂ is its corresponding specific quantity;

_NFC is the total number of electric vehicles using high-power charging equipment;

P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window;

P _chs (j) is the expected comprehensive charging station load of the grid in the j time window;

in,

λ represents the efficiency coefficient of the integrated charging station to reduce the load peak-valley difference (the exponential function mainly reflects the peak shaving function);

P _r0 (j) is the reward price obtained by the integrated charging station in the j time window by reducing the load peak-to-valley difference, and the reward price is negative;

T is the number of time windows, take T=24/Δt;

Preferably, this embodiment adopts but is not limited to an exponential function with P _DR as a variable for the revenue f ₀ obtained by the station participating in the demand response, and can also adopt various types of functions such as quadratic function and logarithmic function to achieve a better fit. the effect of demand objectives;

2) Establish a high-power fast-charging station revenue model, specifically:

in,

P _r4 (j) is the electricity purchase price of the high-power fast charging station through the power grid in the j time window, and the electricity purchase price is negative;

P _r3 (j) is the high-power charging electricity price of the electric vehicle in the j time window, and the charging electricity price is negative;

3) Establish a V2G station revenue model, specifically:

in,

P _r1 (j) is the electricity price for the charging station to purchase or sell electricity through the power grid in the j time window, the electricity purchase price is negative, and the electricity sales price is positive;

P _r2 (j) is the charging or discharging electricity price of the electric vehicle in the j time window, the charging electricity price is negative, and the discharging electricity price is positive;

P _ev (i,j) is the operating power of the i-th charging pile in the j time window, charging is positive and discharging is negative;

Δt represents a scheduling time window;

3-1) Establish a comprehensive charging station revenue model, specifically:

F _S =a ₀ f ₀ +a ₁ f ₁ +a ₂ f ₂

in,

a ₀ , a ₁ , and a ₂ are the demand response revenue of the site, the revenue model, and the weight factor of the V2G site revenue, respectively, a ₀ +a ₁ +a ₂ =1;

3-2) Establish a V2G user benefit model, specifically:

a) The charging expenditure of the user's electric vehicle is:

b) The psychological subsidy f _C1 for depreciation of the user's electric vehicle power battery due to non-travel discharge behavior is:

When P _ev (i,j)>0, f _C1 =0;

When P _ev (i,j)<0,

in,

β is the depreciation subsidy price coefficient for battery discharge, which is negative;

3-3) The expenses of charging/discharging behavior of V2G users are comprehensively obtained as:

F _C =f _C0 +f _C1 ;

4) The energy management scheduling optimization objective of the integrated charging station is as follows:

min F=(-F _S , F _C ) ^T ;

The specific solution and calculation method of the variable of the target minimum value and the steps thereof are well known to those skilled in the art, and are not described in detail in the present invention.

The above embodiments are only to illustrate the technical concept and characteristics of the present invention, and their purpose is to allow those familiar with the art to understand the content of the present invention and implement it, and cannot limit the scope of protection of the present invention. Equivalent changes or modifications made should all be included within the protection scope of the present invention.

Claims (14)

1. a V2G charging station system based on an edge computing platform, is characterized in that: Charging scheduling management control and operation system: It is composed of a charging scheduling management control platform and a charging operation platform. The charging scheduling management control platform receives the electrical status data of the smart terminals in the grid station area, the user demand information of the charging operation platform, and the pile group scheduling control. The system's pile group operation status information and control strategy information and the power grid scheduling requirement information of the upper-level power grid dispatching control system, formulate the operation strategy and send it to the lower-level pile group as an execution reference, and the charging operation platform receives the charging order information and charging discount/subsidy behavior information Calculate charging discounts/subsidies, perform charging fee settlement and notify users to perform settlement, receive charging demand information from the user's charging application and send it to the overall charging scheduling management and control platform, receive charging plan information from the charging scheduling management and control platform, and send it to the user's charging application For users to know, the charging scheme information includes the following steps: 1) The user manually enters or presets the target SOC value of the current charging through the user charging application terminal, which is recorded as SOC ₁ ; 2) Estimate the charging time of the three charging schemes, namely: ① Ordinary charging, that is, the electric vehicle is charged immediately after starting the charging until the charging service stops because the power battery is full; ② Off-peak charging, that is, based on ordinary charging, if the charging period is After the peak electricity price of the grid, the charging will be temporarily stopped until the charging service is stopped because the power battery is full during the off-peak electricity price period; ③Economic charging, that is, during the charging period, the electric vehicle first feeds power to the grid to the set allowable discharge depth during the peak electricity price period , and recharge to the user's target SOC; 3) Estimate the amount of charging discount for the three charging schemes; 4) Push the estimation results of the three charging schemes to the user's charging application; 5) The user selects the charging scheme; 6) If the user participates in the V2G response, the energy management scheduling method of the V2G charging station is invoked to generate a charging plan; if the user does not participate in the V2G response, the charging plan is generated according to the charging plan selected by the user; 7) Execute the charging plan according to the scheduling control quantity P _ev-opt(i,j) ; 8) Each corresponding charging device responds to the charging plan instruction; 9) After a certain interval of time after the response of the previous step, if the charging of the electric vehicle connected to the charging device is completed, end the charging function of the corresponding device and submit it to the user for settlement. one step; 10) Judging whether the charging plan parameters in the field station have changed, when there is a change, return to step 6)-8); when there is no change, continue to execute the current charging plan, and the charging plan parameters include the user changing the departure time, Emergency stop of charging and grid scheduling commands for some reason. 2. The V2G charging station system based on the edge computing platform according to claim 1, characterized in that: it further comprises a power grid dispatching control system: receiving the regional charging operation information of the charging dispatching management and control general platform, and sending the coordinated dispatching information, so that the The cooperative scheduling information is demand response, station load forecasting, scheduling response strategy, etc. 3. The V2G charging station system based on the edge computing platform according to claim 1, characterized in that: it also includes a pile group scheduling control system: uploading the status information and control strategy information of the pile group operation to the upper-level charging scheduling management control system. The platform receives the electric vehicle charging and discharging operation information of the lower-level charging pile group system, and formulates an operation strategy and sends it to each lower-level charging pile for execution in combination with the requirements issued by the upper-level charging scheduling management and control platform. 4. The V2G charging station system based on an edge computing platform according to claim 1, characterized in that: further comprising a charging pile group system: collecting electric vehicle charging and discharging operation information, and simultaneously sending it to the edge objects of the pile group dispatching control system The charging operation platform, which is connected with the agent computing platform and the charging scheduling management control and operation system, accepts and executes the charging and discharging instructions of the charging pile connected to the electric vehicle issued by the superior system. 5 . The V2G charging station system based on an edge computing platform according to claim 1 , wherein the range of the grid station area is a single distribution network area with voltage levels of 110kV, 10kV and 380V. 6 . 6. The V2G charging station system based on an edge computing platform according to claim 1, characterized in that: in step 2), estimating the charging time of the three charging schemes includes: 1) Equivalent discharge at constant rated power, that is, the equivalent discharge amount from the current SOC of the electric vehicle to the allowable depth of discharge, and the shortest time t _{chp0 required} :

in, SOC ₀ is the SOC value when the electric vehicle starts to charge; D ₀ is the allowable depth of discharge for electric vehicles; P _V2G-dch is the rated discharge power of the V2G charging pile; It should be noted that the rated charging/discharging power of the electric vehicle should not be less than the rated charging/discharging power of the charging pile; 2) The whole process of charging the electric vehicle to SOC ₁ consists of two stages, in which there is a critical value SOC _vb of the SOC related to the battery voltage of the electric vehicle; a) If SOC ₁ ≤ SOC _vb , charge with constant power throughout the whole process: The normal charging process duration t _chp1 is:

The process duration t _chp2 of deep charging is:

b) If SOC ₁ >SOC _vb , charge with constant power when SOC≤SOC _vb , and charge with constant voltage when SOC>SOC _vb : The normal charging process duration t _chp3 is:

The duration of the deep charging process t _chp4 is:

in, P _V2G-ch is the rated charging power of the V2G charging pile; P _V2G-ch (t) is a function of the charging power of the V2G charging pile in the constant voltage charging state as a function of time; 3) Estimated value of ordinary charging time: If SOC ₁ ≤SOC _vb , then t _ch1 =t _chp1 If SOC ₁ >SOC _vb , then t _ch1 =t _chp3 4) Estimated off-peak charging time: If T ₀ +t _ch1 ≤T _pop , then t _ch2 =t _ch1 If T ₀ +t _ch1 >T _pop , then t _ch2 =t _ch1 +t _pop in, t _pop is the duration of the grid peak electricity price that is closest to the charging start time T ₀ and starts at time T _pop ; 5) Estimated value of economical charging time: a) When t _chp0 >t _pop , that is, when the electric vehicle cannot be discharged to D ₀ at a constant rated power during the equivalent peak electricity price, there is an estimated value A of the economical charging time If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp1 +(1+SC _dch-ch )t _pop If SOC ₁ >SOC _vb , then t _ch3 =t _chp3 +(1+SC _dch-ch )t _pop b) When t _{chp0 ≤} t _pop , that is, when the electric vehicle can be discharged to D ₀ with constant rated power during the equivalent peak electricity price, there is an economical charging time estimate B If SOC ₁ ≤SOC _vb , then t _ch3 =t _chp2 +t _pop If SOC ₁ >SOC _vb , then t _ch3 =t _chp4 +t _pop in, SC _dch-ch is the ratio of the rated discharge power to the rated charging power of the V2G charging pile. 7. The V2G charging station system based on the edge computing platform according to claim 6, wherein the step 3) estimating the charging discount amount of the three charging schemes comprises the following steps: 1) the normal charging and the off-peak charging The charging discount is 0 2) The charging discount for economical charging is υ*t _pop 3) Calculate the charging cost of the plan a) Ordinary charging fee:

b) Off-peak charging fee:

c) Economic charging fee:

in, P _r (j) the high-power charging electricity price of the electric vehicle in the j time window, and the charging electricity price is negative; P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window; T _ch1 =t _ch1 /Δt, T _ch2 =t _ch2 /Δt, T _pop =t _pop /Δt. 8. The V2G charging station system based on an edge computing platform according to claim 7, characterized in that: in step 4), pushing the estimation results of the three charging schemes to the user charging application terminal comprises the following steps: adding the ordinary charging [ t _ch1 ,cst _ch1 ], off-peak charging [t _ch2 ,cst _ch2 ] and economical charging [t _ch3 ,cst _ch3 ] are pushed to the user charging application side. 9. The V2G charging station system based on an edge computing platform according to claim 8, wherein the charging scheme selected by the user in step 5) comprises the following steps: 1) If the ordinary charging scheme and the off-peak charging scheme are adopted, the user does not participate in the V2G response; 2) If the economical charging scheme is adopted, then: a) When T ₀ +t _ch3 ≤T _s , temporarily judge that the user can participate in the V2G response; b) When T ₀ +t _ch3 >T _s , temporarily judge that the user cannot participate in the V2G response; 3) Among them, the user can input the scheduled departure time at any time during the charging period. If the user inputs the scheduled departure time, set T _s as the user scheduled departure time; if the user does not input the scheduled departure time, set T s as the scheduled departure time. Set T _s as the estimated charging time of the scheme. 10. The V2G charging station system based on an edge computing platform according to claim 1, wherein the charging plan of the step 6) comprises the following steps: 1) Establish a grid-side demand response model of the V2G charging station, where the grid-side demand response model includes: a) The expected effect of the station participating in the grid-side demand response:

in, N is the total number of electric vehicles; g ₁ is the proportion of electric vehicles that can participate in the V2G response scheduling strategy; N ₁ is its corresponding specific quantity; g ₂ is the proportion of electric vehicles that do not participate in the V2G response scheduling strategy, g ₂ =1-g ₁ ; N ₂ is its corresponding specific quantity; P _ev (i,j) is the charging power generated by the i-th electric vehicle j time window; P _chs (j) is the expected V2G charging station load of the grid in the j time window; b) The benefits of the station participating in the grid-side demand response:

in, λ(P _DR ) represents the efficiency function of the V2G charging station to reduce the load peak-to-valley difference, and reflects the effect of the station on the grid-side demand response in the form of revenue; P _r0 (j) is the reward price obtained by the V2G charging station in the j time window by reducing the load peak-to-valley difference, and the reward price is negative; T is the number of time windows, T=24/Δt; 2) Operational revenue model of V2G charging station, the operational revenue model includes:

in, P _r1 (j) is the electricity price for the charging station to purchase or sell electricity through the power grid in the j time window, the electricity purchase price is negative, and the electricity sales price is positive; P _r2 (j) is the charging or discharging electricity price of the electric vehicle in the j time window, the charging electricity price is negative, and the discharging electricity price is positive; P _ev (i,j) is the operating power of the i-th charging pile in the j time window, charging is positive and discharging is negative; Δt represents a scheduling time window; 3) Comprehensive income model of V2G charging station, the comprehensive income model includes: F _S =a ₀ f ₀ +a ₁ f ₁ ; in, a ₀ and a ₁ are the weighting factors of the demand response revenue of the site and the revenue of the V2G site, respectively, a ₀ +a ₁ =1; 4) Establish a V2G user benefit model, which includes: a) The charging expenditure of the user's electric vehicle is:

b) The psychological subsidy f _C1 for depreciation of the user's electric vehicle power battery due to non-travel discharge behavior is: When P _ev (i,j)>0, f _C1 =0; When P _ev (i,j)<0,

in, β is the depreciation subsidy price coefficient for battery discharge, which is negative; c) The cost of comprehensively obtaining the charging/discharging behavior of V2G users is: F _C =f _C0 +f _C1 ; 5) V2G charging station energy management scheduling optimization objectives, the scheduling optimization objectives include: F∈max F _S ∩min F _C ; When the dual goals of maximizing V2G charging station revenue and minimizing user charging expenditures can be met at the same time, the charging/discharging power P _ev-opt(i,j) of the i-th electric vehicle j time window is the scheduling control quantity, The energy management scheduling optimization objective can be transformed into a single objective with respect to satisfying the minimum of the binary variables F _S and F _C : min _F =(-FS , _FC ) ^T . 11. The V2G charging station system based on an edge computing platform according to claim 1, characterized in that: the types of charging piles to which the pile group scheduling control system belongs are AC charging piles, DC charging piles, V2G charging piles, charging piles Any one or more of stacks, charging bows, and automatic charging devices. 12. The V2G charging station system based on an edge computing platform according to claim 1, characterized in that: the dispatching management control system of the charging station is used as the dispatching management controller of the charging station or the regional charging station. Jurisdiction over multiple edge IoT proxy computing platforms. 13. The V2G charging station system based on an edge computing platform according to claim 1, wherein the scheduling management control system of the charging station is calculated by a plurality of charging pile group systems through respective edge IoT agents The platform consists of multiple sub-pile group dispatching control systems, which are uniformly connected to the dispatching management and control system of the charging station to receive control. 14. The V2G charging station system based on an edge computing platform according to claim 1, wherein the form of the user charging application terminal comprises a mobile phone APP, a charging pile touch screen, voice recognition software and hardware, and smart home equipment, Data interaction is realized by connecting directly or indirectly to the charging operation platform through physical communication means, including Ethernet, 3G\4G\5G wireless communication, and local area network.

Images