CN112590601A - Novel V2G charging station system based on edge computing platform and charging method thereof - Google Patents

Novel V2G charging station system based on edge computing platform and charging method thereof Download PDF

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CN112590601A
CN112590601A CN202011547889.7A CN202011547889A CN112590601A CN 112590601 A CN112590601 A CN 112590601A CN 202011547889 A CN202011547889 A CN 202011547889A CN 112590601 A CN112590601 A CN 112590601A
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charging
user
station
scheduling
platform
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CN112590601B (en
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贾俊国
张珂宸
周凌霄
史剑
冯中魁
李悦
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State Grid Smart Energy Traffic Technology Innovation Center Suzhou Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/68—Off-site monitoring or control, e.g. remote control
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles

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  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
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Abstract

The invention discloses a novel V2G charging station system based on an edge computing platform and a charging method thereof, which are composed of a charging pile group system, a pile group scheduling control system, a charging scheduling management control and operation system and a power grid scheduling control system, and can not only recommend a charging scheme for users intelligently, but also strive for the maximum charging profit for users staying for a long time through scheduling optimization of stations based on the edge computing platform.

Description

Novel V2G charging station system based on edge computing platform and charging method thereof
Technical Field
The invention relates to the technical field of electric automobile charging, in particular to a novel V2G charging station system based on an edge computing platform and a charging method thereof.
Background
The environmental protection and economic benefits of the electric automobile are obvious, but the influence brought by the connection of the electric automobile to a power grid cannot be ignored as the market share of the electric automobile is gradually improved. The charging load of the electric vehicle is different from other traditional power loads in the power system, and when a reasonable scheduling strategy is lacked, especially in a scene of gathering high-power charging and peak charging, the random charging behavior of a user is very likely to cause 'peak-to-peak' of a power grid and even generate a new power consumption peak, thus the load on the power system is increased, and the power grid paralysis is likely to be caused directly.
Meanwhile, the charging behavior of the power consumption peak of the power grid also enables a charging user to bear higher charging expenditure, so that the risk that the attraction of a charging station needs to bear the power limiting of the power grid is reduced. A large number of research and investigation results have shown that a proportion of private vehicles of around 90% are only around 1 hour of daily travel time, i.e. most vehicles spend a considerable amount of time in an idle state. Therefore, in the field of intelligent transportation, Vehicle-to-Grid (V2G) reasonably regulates charging and feeding behaviors of the electric Vehicle through V2G bidirectional interaction between the power Grid and electric Vehicle users, namely, various negative effects possibly caused by the Vehicle-to-Grid can be effectively reduced, and 'peak clipping and valley filling' is performed on the power Grid; the energy storage characteristic of the vehicle-mounted battery of the electric automobile can be fully exerted, the vehicle-mounted battery is selectively connected to charge and store energy in the low-load and low-electricity-price periods of the power grid, and the reverse feed is selectively connected to the vehicle-mounted battery in the peak-load and high-electricity-price periods of the power grid, so that the charging expenditure of a user is stabilized or reduced while the high-power quick charging service quality of a station is ensured, and the operation cost and pressure are effectively reduced.
The existing V2G charging station has the following disadvantages:
1. the existing V2G charging station system can not be separated from the load prediction result of the power grid system of the same platform area, and the energy management scheduling system of the charging station takes on more power grid scheduling functions, so that the system redundancy is complicated.
2. The existing V2G charging station does not comprehensively consider how the comprehensive station balances the stability of a power grid, the operation profit of the station and the charging cost of a user for scheduling and management.
3. The high-power direct-current charging pile becomes an absolute leading role in public/commercial charging service, but the power consumption peak caused by aggregated charging and peak charging is aggravated by the pure high-power direct-current charging pile, and the rapid large-scale development of the high-power direct-current charging pile is limited.
4. The peak-valley time period is a relatively fixed power grid, and the feeding of the electric vehicle is reasonably arranged in a pure V2G charging station, so that the peak clipping effect is obvious; however, the battery capacity of the electric automobile is limited, and the effect of 'valley filling' of a pure V2G charging station through an ordered charging mode is the same as that of a common medium-power and low-power charging station.
Disclosure of Invention
In order to overcome the defects, the invention aims to provide a novel V2G charging station system based on an edge computing platform and a charging method thereof, wherein the charging station system can intelligently recommend a charging scheme for a user and can also strive for the maximum charging profit for the user staying for a long time through scheduling optimization of stations.
In order to achieve the above purposes, the invention adopts the technical scheme that: a novel V2G charging station system based on an edge computing platform and a charging method thereof are characterized by comprising four layers of systems:
charging pile group system: collecting charging and discharging operation information of the electric automobile, simultaneously sending the charging and discharging operation information to an edge internet of things agent calculation platform of a pile group dispatching control system and a charging operation platform of a charging dispatching management control and operation system, and receiving and executing a charging and discharging instruction of a charging pile connected with the electric automobile and issued by a superior system;
pile group scheduling control system: uploading the running state information and the control strategy information of the pile group to an upper charging dispatching management control general platform, receiving the charging and discharging running information of the electric vehicle of a lower charging pile group system, and formulating a running strategy to be sent to each lower charging pile to be executed by combining the requirements issued by the upper charging dispatching management control general platform;
charging scheduling management control and operation system: the system is composed of two physically separated subsystems of a charging dispatching management control main platform and a charging operation platform, information mutual transmission and intercommunication is realized between the subsystems in a wired or wireless network mode, the charging dispatching management control main platform receives electrical state data of an intelligent terminal of a power grid platform area, user demand information of the charging operation platform, pile group operation state information and control strategy information of a pile group dispatching control system and power grid dispatching requirement information of a superior power grid dispatching control system, an operation strategy is formulated and sent to a subordinate pile group as an execution reference, the charging operation platform receives charging order information and charging discount/subsidy behavior information to calculate charging discount/subsidy, charges are settled to inform a user to execute settlement, charging demand information of a charging application end of the user is received and sent to the charging dispatching management control main platform, and charging scheme information of the charging dispatching management control main platform is received, sending the information to a user charging application terminal so that a user can know the information;
the power grid dispatching control system comprises: receiving regional charging operation information of a charging scheduling management control overall platform, and sending cooperative scheduling information, such as demand response, platform load prediction and scheduling response strategies.
Further, the power grid region ranges from a single power distribution grid region with 110kV, 10kV and 380V voltage levels.
Further, the charging scheme information includes the steps of:
1) the user records the target SOC value of the current charging as the SOC through manual input or preset in the user charging application terminal1；
2) The charging times for the three charging schemes were estimated, respectively: firstly, ordinary charging, namely starting charging immediately to charge the electric automobile until the power battery is fully charged and the charging service is stopped; secondly, off-peak charging, namely based on common charging, if the peak power price of the power grid is experienced during the charging period, the charging is temporarily stopped until the charging service is stopped because the power battery is fully charged during the off-peak power price period; thirdly, economic charging, namely, the electric automobile feeds power to the power grid to a set allowable discharging depth in the peak electricity price period in the charging period and recharges the power to the target SOC of a user;
3) estimating charge discount amounts of the three charging schemes;
4) pushing estimation results of the three charging schemes to a user charging application terminal;
5) a user selects a charging scheme;
6) if the user participates in the V2G response, an energy management scheduling method of the V2G charging station is called to generate a charging plan, and if the user does not participate in the V2G response, the charging plan is generated according to the charging scheme selected by the user.
7) According to the scheduling control quantity Pev-opt(i,j)A charging plan is executed.
8) And the corresponding charging equipment responds to the charging plan instruction.
9) And after a certain interval time after the response of the last step, if the charging of the electric automobile connected with the charging equipment is completed, ending the charging function of the corresponding equipment and submitting the charging function to a user for settlement, and if the charging is still completed, determining that the charging plan is not completed, and entering the next step.
10) Judging whether the charging plan parameters in the station are changed or not, and returning to execute the steps 6) -8) when the charging plan parameters are changed; and when the charging time is not changed, the current charging plan is continuously executed, and the parameters of the charging plan comprise the changing of the off-site time of the user, emergency stop of charging due to reasons and a power grid dispatching command.
Further, the charging plan of step 6) includes the following steps:
1) establishing a power grid side demand response model of the V2G charging station, wherein the power grid side demand response model comprises the following steps:
a) the station participates in the predicted effect of the power grid side demand response:
Figure BDA0002856219630000041
wherein the content of the first and second substances,
n is the total number of the electric automobiles;
g1the proportion of electric vehicles which can participate in the V2G response scheduling strategy;
N1the specific number corresponding thereto;
g2fraction of electric vehicles not participating in V2G response scheduling policy, g2＝1-g1；
N2The specific number corresponding thereto;
Pev(i,j)generating charging power for the j time window of the ith electric vehicle;
Pchs(j)charging station load for the desired V2G for the grid for the j time window;
b) and (3) the yield of the station participating in the power grid side demand response:
Figure BDA0002856219630000051
wherein the content of the first and second substances,
λ(PDR) The efficiency function of the V2G charging station for reducing load peak-valley difference is shown, and the effect of the station on the power grid side demand response is reflected in a profit mode;
Pr0awarding a price for the charging station by reducing the load peak to valley difference for a time window of j V2G, the prize price being negative;
t is the number of time windows, and T is 24/delta T;
2) the V2G charging station operation income model comprises:
Figure BDA0002856219630000052
wherein the content of the first and second substances,
Pr1(j)the electricity purchasing price or the electricity selling price of the charging station is negative and the electricity selling price is positive in the j time window;
Pr2(j)the charging or discharging electricity price of the electric automobile in the j time window is negative, and the discharging electricity price is positive;
Pev(i,j)the charging is positive and the discharging is negative for the operation power of the ith charging pile in the j time window;
Δ t represents a scheduling time window;
3) the V2G charging station integrated revenue model, the integrated revenue model comprising:
FS＝a0f0+a1f1；
wherein the content of the first and second substances,
a0、a1weighting factors, a, for the demand response returns and V2G station returns of a station, respectively0+a1＝1；
4) Establishing a V2G user revenue model, wherein the user revenue model comprises:
a) the charging expenditure of the user electric automobile is as follows:
Figure BDA0002856219630000061
b) psychological patch f for depreciation of power battery of user electric automobile caused by non-trip discharge behaviorC1Comprises the following steps:
when P is presentev(i,j)>At 0, fC1＝0；
When P is presentev(i,j)<At the time of 0, the number of the first,
Figure BDA0002856219630000062
wherein the content of the first and second substances,
beta is depreciation subsidy price coefficient of battery discharge and is a negative value;
c) the cost of integrating the charge/discharge behavior of the V2G user is:
FC＝fC0+fC1；
5) V2G charging station energy management scheduling optimization objective, the scheduling optimization objective comprising:
F∈max FS∩min FC；
when the dual targets of maximizing the income of the V2G charging station and minimizing the charging expense of the user can be simultaneously met, the charging/discharging power P of the ith electric vehicle j time windowev-opt(i,j)Is a scheduling control quantity that can translate the energy management scheduling optimization objective with respect to satisfying a binary variable FSAnd FCSingle target of minimum value of:
min F＝(-FS,FC)T。
further, the pile group dispatching control system belongs to any one or more of an alternating current charging pile/a direct current charging pile/V2G charging pile/a charging arch/automatic charging equipment.
Furthermore, the scheduling management control system of the charging station is used as a scheduling management controller of the charging station or the regional charging station, and manages a plurality of edge internet of things agent computing platforms.
Furthermore, the dispatching management control system of the charging station is composed of a plurality of charging pile group systems and a plurality of sub-pile group dispatching control systems formed by respective edge internet of things agent computing platforms, and the dispatching management control systems which are connected to the charging station in a unified mode are controlled.
Furthermore, the form of the user charging application end comprises a mobile phone APP, a charging pile touch screen, voice recognition software and hardware and intelligent household equipment, the mobile phone APP is directly or indirectly connected to the charging operation platform through a physical communication means to realize data interaction, and the physical communication means comprises an Ethernet, 3G \4G \5G wireless communication and a local area network.
Compared with the prior art, the invention has the beneficial effects that:
1. the novel charging scheduling management control system for the V2G station is flexible in configuration mode, and can manage and control the charging scheduling of the station by relying on a charging scheduling management control main platform or a marginal Internet of things agent computing platform according to different requirements.
2. The novel V2G charging starting control and energy scheduling control method makes up for the fact that the charging starting is complicated because the current V2G charging energy scheduling method must first ask for charging behavior parameters, and improves user friendliness by adopting a recommended intelligent scheme.
3. The novel energy scheduling method for the V2G charging station considers the requirements of peak clipping and valley filling of a power grid, the operation income of the charging station and the rights and interests of V2G charging users, improves the reliability of station scheduling management and reduces the time delay of the station scheduling management by relying on the quick response of edge calculation.
4. The comprehensive charging station can not only meet the requirement that a V2G user earns feedback to the power grid feed, but also obtain charging discount or subsidy to high-power charging equipment of the same station by providing power, and complement the peak clipping function of V2G and the valley filling function of high-power charging, thereby effectively stabilizing the load of the power grid.
Drawings
Fig. 1 is a schematic diagram of a charging schedule management control system;
FIG. 2 is a flow chart of a startup control and an energy dispatch control;
FIG. 3 is a flow chart of a charging duration for developing an estimated charging profile for a charging profile;
FIG. 4 is a flow chart of estimating charge for a charging schedule based on charge duration in formulating a charging schedule;
FIG. 5 is a schematic diagram of an electrical system;
fig. 6 is a schematic structural diagram of an electrical system.
In the figure:
1-charging pile group system; 2-pile group scheduling control system; 3-a charging scheduling management control and operation system; 4-a charging scheduling management control and operation system; 5-high power charging equipment; 6-V2G charging equipment; 7-total bus of the system; 8-the sub-bus of the access device 7.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention.
Referring to the attached fig. 1, the novel V2G station charging scheduling management control system based on the edge computing platform is composed of four layers of systems:
charging pile group system 1: collecting charging and discharging operation information of the electric automobile, such as the charging and discharging state of the electric automobile, the expected charging amount of a user, the estimated stay time and the like, and simultaneously sending the information to an edge Internet of things agent calculation platform of the pile group dispatching control system and a charging operation platform of a charging dispatching management control and operation system; receiving and executing charging and discharging instructions and the like of a charging pile accessed by the electric automobile and issued by a superior system;
pile group scheduling control system 2: uploading the state information and the control strategy information of pile group operation to an upper-level charging scheduling management control main platform; receiving the charging and discharging operation information of the electric automobile of the lower charging pile group system, combining the requirements issued by the upper charging dispatching management control main platform, formulating an operation strategy and sending the operation strategy to each lower charging pile for execution;
charging schedule management control and operation system 3: the system is composed of two physically separated subsystems of a charging scheduling management control main platform and a charging operation platform, and information is mutually communicated between the subsystems in a wired or wireless network mode. The charging dispatching management control main platform receives electrical state data of an intelligent terminal of a power grid area, user demand information of a charging operation platform, pile group running state information and control strategy information of a pile group dispatching control system and power grid dispatching requirement information of a superior power grid dispatching control system, formulates a running strategy and sends the running strategy to a subordinate pile group as an execution reference; the charging operation platform receives the charging order information and the charging discount/subsidy behavior information, calculates the charging discount/subsidy, and carries out charging fee settlement to inform the user of executing settlement; receiving charging demand information of a user charging application terminal and sending the charging demand information to a charging scheduling management control main platform; receiving charging scheme information of a charging scheduling management control overall platform, and sending the charging scheme information to a user charging application terminal so that a user can know the charging scheme information;
the power grid dispatching control system 4: receiving regional charging operation information of a charging scheduling management control overall platform, and sending cooperative scheduling information, such as demand response, load prediction, scheduling response strategy and the like.
Further, the grid area ranges from a single distribution grid area of 110kV, 10kV and 380V voltage class.
Further, the type of the charging pile to which the pile group dispatching control system belongs may be various types such as an alternating current charging pile, a direct current charging pile, a V2G charging pile, a charging arch, an automatic charging device and the like, and may also be a mixture of various types of charging piles.
Further, the charging scheduling management control main platform is usually used as a scheduling management controller of a charging station or a regional charging station, and manages a plurality of edge internet of things agent computing platforms (i.e. a pile group scheduling control system).
In an extensible manner, the scheduling management control system of one charging station can be formed by a plurality of different charging pile group systems constructed in multiple purposes through respective edge internet of things agent computing platforms to form a plurality of sub-pile group scheduling control systems, and the sub-pile group scheduling control systems are connected to the charging scheduling management control main platform in a unified mode to be controlled. The dispatching management control system of the regional charging station can only uniformly connect a plurality of charging devices of a plurality of types to the edge Internet of things agent computing platform to receive the control of the corresponding station, and then uniformly manage and control the connected charging station by the charging dispatching management control main platform.
Furthermore, the charging application end of the user can be in the form of a mobile phone APP, a charging pile touch screen, voice recognition software and hardware, intelligent household equipment and the like, and is directly or indirectly connected to the charging operation platform through physical communication means such as Ethernet, 3G \4G \5G wireless communication, local area network and the like to realize data interaction.
Furthermore, the edge internet of things agent computing platform (namely a pile group scheduling control system) provides a novel V2G charging starting control and energy scheduling control method, the method makes up for the fact that the charging starting is complicated because the charging behavior parameters must be firstly requested in the current V2G charging energy scheduling method, and the user friendliness is improved by adopting a recommended intelligent scheme;
1) the user records the target SOC value of the current charging as the SOC through manual input or preset in the user charging application terminal1；
2) The charging times for the three charging schemes, as shown in fig. 2, were estimated, and the proposed three charging schemes based on V2G, respectively: firstly, ordinary charging, namely starting charging immediately to charge the electric automobile until the power battery is fully charged and the charging service is stopped; secondly, off-peak charging, namely based on common charging, if the peak power price of the power grid is experienced during the charging period, the charging is temporarily stopped until the charging service is stopped because the power battery is fully charged during the off-peak power price period; thirdly, economic charging, namely, the electric automobile feeds power to the power grid to a set allowable discharging depth in the peak electricity price period in the charging period and recharges the power to the target SOC of a user;
2-1) constant rated power equivalent discharge, namely the equivalent discharge amount of the electric automobile discharging to the allowable discharge depth from the current SOC, and the required minimum time tchp0：
Figure BDA0002856219630000101
Wherein the content of the first and second substances,
SOC0is the SOC value when the electric automobile starts to charge;
D0is the allowable depth of discharge of the electric vehicle;
PV2G-dchis the rated discharge power of the V2G charging pile;
specifically, the rated charge/discharge power of the electric automobile should be not less than the rated charge/discharge power of the charging pile;
2-2) charging the electric vehicle to SOC1Consists of two stages, in which there is a critical value SOC of SOC relative to the battery voltage of the electric vehiclevb；
a) If SOC1≤SOCvbAnd then, charging at constant power in the whole process:
duration t of ordinary charging processchp1Comprises the following steps:
Figure BDA0002856219630000111
duration t of deep charging processchp2Comprises the following steps:
Figure BDA0002856219630000112
b) if SOC1>SOCvbWhen SO is generatedC≤SOCvbCharging at constant power while charging at SOC>SOCvbCharging with constant voltage:
duration t of ordinary charging processchp3Comprises the following steps:
Figure BDA0002856219630000113
duration t of deep charging processchp4Comprises the following steps:
Figure BDA0002856219630000114
wherein the content of the first and second substances,
PV2G-chis the rated charging power of the V2G charging pile;
PV2G-ch(t)is a function of the charging power of the V2G charging post in a constant voltage charging state, as a function of time;
2-3) general charge duration estimate:
if SOC1≤SOCvbThen t isch1＝tchp1
If SOC1>SOCvbThen t isch1＝tchp3
2-4) estimated off-peak charging time:
if T0+tch1≤TpopThen t isch2＝tch1
If T0+tch1>TpopThen t isch2＝tch1+tpop
Wherein the content of the first and second substances,
tpopis a distance from the start time of charging T0Most recently, starting at time TpopThe duration of the peak electricity price of the power grid;
2-5) economic charge duration estimate:
a) when t ischp0>tpopThat is, the electric vehicle cannot discharge to D at a constant rated power during the equivalent peak electricity price0Sometimes, there is an economic charging duration estimation value A
If SOC1≤SOCvbThen t isch3＝tchp1+(1+SCdch-ch)tpop
If SOC1>SOCvbThen t isch3＝tchp3+(1+SCdch-ch)tpop
b) When t ischp0≤tpopThat is, the electric vehicle can discharge to D at constant rated power during the equivalent peak electricity price0Sometimes, there is an economical charging duration estimation value B
If SOC1≤SOCvbThen t isch3＝tchp2+tpop
If SOC1>SOCvbThen t isch3＝tchp4+tpop
Wherein the content of the first and second substances,
SCdch-chis the ratio of the rated discharge power and the rated charge power of the V2G charging pile;
3) referring to fig. 3, charge discount amounts for three charging schemes are estimated,
3-1) Charge discount of ordinary Charge and off-Peak Charge is 0
3-2) charge discount for economical charging upsilontpop
3-3) calculating the charging cost of the scheme
a) Ordinary charging cost:
Figure BDA0002856219630000121
b) off-peak charging cost:
Figure BDA0002856219630000131
c) economic charging cost:
Figure BDA0002856219630000132
wherein the content of the first and second substances,
Tch1＝tch1/Δt、Tch2＝tch2/Δt、Tpop＝tpop/Δt；
4) the results of the estimation of the three charging schemes: ordinary charging [ tch1,cstch1]Off peak charging [ tch2,cstch2]And economical charging [ t ]ch3,cstch3]Pushing to a user charging application terminal;
5) the user selects a charging scheme to be used,
5-1) if a common charging scheme and a non-peak charging scheme are adopted, the user does not participate in the V2G response;
5-2) if an economical charging scheme is adopted, then:
a) when T is0+tch3≤TsTemporarily, it is determined that the user may participate in the V2G response;
b) when T is0+tch3>TsTemporarily determining that the user is not available to participate in the V2G response;
5-3) wherein, the user can input the preset off-field time at any time during the charging period, if the user inputs the preset off-field time, the T is setsPresetting departure time for a user; if the user does not input the preset off-field time, setting TsAn estimated charge time for the scenario;
6) if the user participates in the V2G response, calling an energy management scheduling method of the V2G charging station to generate a charging plan; if the user does not participate in the V2G response, generating a charging plan according to the charging scheme selected by the user;
the method comprises the steps that an energy management scheduling method is called to generate a bearing platform of a charging plan, and the bearing platform is determined according to whether the role of a scheduling management control system is a marginal Internet of things agent computing platform or a charging scheduling management control total platform;
further, referring to fig. 4, a charging energy scheduling method considering grid "peak clipping and valley filling", station operation income and V2G user rights and interests is provided, which specifically includes:
6-1) establishing a power grid side demand response model of the V2G charging station, which specifically comprises the following steps:
a) the station participates in the predicted effect of the power grid side demand response:
Figure BDA0002856219630000141
wherein the content of the first and second substances,
n is the total number of the electric automobiles;
g1the proportion of electric vehicles which can participate in the V2G response scheduling strategy;
N1the specific number corresponding thereto;
g2fraction of electric vehicles not participating in V2G response scheduling policy, g2＝1-g1；
N2The specific number corresponding thereto;
Pev(i,j)generating charging power for the j time window of the ith electric vehicle;
Pchs(j)charging station load for the desired V2G for the grid for the j time window;
b) and (3) the yield of the station participating in the power grid side demand response:
Figure BDA0002856219630000142
wherein the content of the first and second substances,
λ(PDR)the efficiency function of the V2G charging station for reducing load peak-valley difference is shown, and the effect of the station on the power grid side demand response is reflected in a profit mode;
Pr0awarding a price for the charging station by reducing the load peak to valley difference for a time window of j V2G, the prize price being negative;
t is the number of time windows, and T is taken as 24/delta T;
6-2) V2G charging station operation income model specifically is:
Figure BDA0002856219630000143
wherein the content of the first and second substances,
Pr1(j)for purchasing or selling electricity from charging station through the grid in the time window of jThe electricity price is negative when the electricity is purchased and positive when the electricity is sold;
Pr2(j)the charging or discharging electricity price of the electric automobile in the j time window is negative, and the discharging electricity price is positive;
Pev(i,j)the charging is positive and the discharging is negative for the operation power of the ith charging pile in the j time window;
Δ t represents a scheduling time window;
6-3) V2G charging station comprehensive income model specifically is:
FS＝a0f0+a1f1；
wherein the content of the first and second substances,
a0、a1weighting factors, a, for the demand response returns and V2G station returns of a station, respectively0+a1＝1；
6-4) establishing a V2G user revenue model, which specifically comprises the following steps:
a) the charging expenditure of the user electric automobile is as follows:
Figure BDA0002856219630000151
b) psychological patch f for depreciation of power battery of user electric automobile caused by non-trip discharge behaviorC1Comprises the following steps:
when P is presentev(i,j)>At 0, fC1＝0；
When P is presentev(i,j)<At the time of 0, the number of the first,
Figure BDA0002856219630000152
wherein the content of the first and second substances,
beta is depreciation subsidy price coefficient of battery discharge and is a negative value; .
c) The cost of integrating the charge/discharge behavior of the V2G user is:
FC＝fC0+fC1；
6-5) V2G charging station energy management scheduling optimization target, specifically:
F∈max FS∩min FC；
namely, the charging/discharging power P of the ith electric vehicle in the time window j can simultaneously meet the dual targets of maximizing the income of the V2G charging station and minimizing the charging expense of the userev-opt(i,j)I.e., the scheduling control amount, the energy management scheduling optimization objective can be converted into a single objective with respect to satisfying the minimum of the binary variables FS and FC:
min F＝(-FS,FC)T；
the specific calculation method and steps for solving the variables of the target minimum are well known to those skilled in the art, and are not described in detail herein;
7) according to the scheduling control quantity Pev-opt(i,j)Executing a charging plan;
8) each corresponding charging device responds to the charging plan instruction;
9) after the response of the last step, a certain interval (for example, 15min) is carried out, if the charging of the electric automobile connected with the charging equipment is completed, the charging function of the corresponding equipment is finished, and the user is submitted to settle accounts; if the charging is still in the charging process, the charging plan is not executed completely, and the next step is carried out;
10) judging whether the charging plan parameters in the station are changed, if so, returning to execute the steps 6) -8); if not, continuing to execute the current charging plan, wherein the charging plan parameters include but are not limited to the changing of the departure time by the user, emergency stop of charging due to reasons, a power grid dispatching command and the like.
Based on the V2G charging station, the invention can also be applied to a comprehensive high-power charging station based on V2G, the high-power charging equipment in the comprehensive station is electrically connected with the V2G charging equipment in a direct or indirect mode, not only the electric automobile earns feedback to the power grid through the V2G, but also the electric energy is provided for the high-power charging equipment during the peak load and the peak electricity price of the power grid to reduce the comprehensive operation cost of the station;
the present embodiment provides two types of typical electrical system configurations suitable for such an integrated charging station;
referring to fig. 5, all V2G devices and high-power charging devices of the station are merged into a bus in parallel, and the rated ampacity of the bus is not less than the total rated ampacity of all the charging devices, i.e. IV2G+IFC≤IBUS；
Referring to fig. 6, a plurality of V2G devices and a high-power charging device are merged into a branch bus I-1 in parallel, a plurality of branch buses I-2, … and I-K similar to the branch bus I-1, to which a plurality of V2G devices and a high-power charging device are connected, are all merged into a total bus I in parallel, and the rated current-carrying capacity of each branch bus should not be less than the rated charging current of the high-power charging device connected with the branch bus, i.e. IFC(k)≤II-k；
Further, the charging energy scheduling method of the integrated charging station specifically comprises the following steps:
1) establishing a power grid side demand response model of the comprehensive charging station, specifically:
Figure BDA0002856219630000171
wherein the content of the first and second substances,
NV2Gis the total number of electric vehicles using V2G charging equipment, namely NV2G＝N1+N2；
g1The proportion of electric vehicles which can participate in the V2G response scheduling strategy;
N1the specific number corresponding thereto;
g2the proportion of electric vehicles not participating in the V2G response scheduling strategy, i.e. g2＝1-g1；
N2The specific number corresponding thereto;
NFCthe total number of the electric vehicles applying the high-power charging equipment;
Pev(i,j)generating charging power for the j time window of the ith electric vehicle;
Pchs(j)a comprehensive charging station load expected for the grid of the j time window;
Figure BDA0002856219630000172
wherein the content of the first and second substances,
lambda represents the efficiency coefficient of the comprehensive charging station for reducing the load peak-valley difference (the exponential function mainly embodies the peak clipping function);
Pr0awarding prices for the integrated charging stations in the j time window by reducing load peak-valley differences, wherein the award prices are negative;
t is the number of time windows, and T is taken as 24/delta T;
preferably, the embodiment obtains the income f for the site participation demand response0Using, but not limited to, PDRThe variable is an exponential function of a variable, and various types of functions such as a quadratic function, a logarithmic function and the like can be adopted to achieve the effect of fitting the demand target more;
2) establishing a high-power rapid charging station profit model, specifically:
Figure BDA0002856219630000181
wherein the content of the first and second substances,
Pr4(j)the method comprises the steps that electricity and power prices are purchased through a power grid in a j time window for a high-power quick charging station, and the electricity and power prices are negative;
Pr3(j)the method comprises the following steps of charging the electric automobile at a high power in a j time window, wherein the charging price is negative;
3) establishing a V2G station revenue model, specifically:
Figure BDA0002856219630000182
wherein the content of the first and second substances,
Pr1(j)the electricity purchasing price or the electricity selling price of the charging station is negative and the electricity selling price is positive in the j time window;
Pr2(j)for electric vehicle in j time windowThe charging or discharging electricity price of (1), the charging electricity price is negative, and the discharging electricity price is positive;
Pev(i,j)the charging is positive and the discharging is negative for the operation power of the ith charging pile in the j time window;
Δ t represents a scheduling time window;
3-1) establishing a comprehensive charging station profit model, which specifically comprises the following steps:
FS＝a0f0+a1f1+a2f2
wherein the content of the first and second substances,
a0、a1、a2weight factors, a, for the demand response returns, return model and V2G station returns, respectively, of a station0+a1+a2＝1；
3-2) establishing a V2G user revenue model, which specifically comprises the following steps:
a) the charging expenditure of the user electric automobile is as follows:
Figure BDA0002856219630000191
b) psychological patch f for depreciation of power battery of user electric automobile caused by non-trip discharge behaviorC1Comprises the following steps:
when P is presentev(i,j)>At 0, fC1＝0；
When in usePev(i,j)<At the time of 0, the number of the first,
Figure BDA0002856219630000192
wherein the content of the first and second substances,
beta is depreciation subsidy price coefficient of battery discharge and is a negative value;
3-3) the payout of the charging/discharging behavior of the V2G user is combined:
FC＝fC0+fC1；
4) the energy management scheduling optimization target of the comprehensive charging station specifically comprises the following steps:
min F＝(-FS,FC)T；
the specific calculation method and steps for solving the variables of the target minimum are well known to those skilled in the art, and are not described in detail herein.
The above embodiments are merely illustrative of the technical concept and features of the present invention, and the present invention is not limited thereto, and any equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of the present invention.

Claims (8)

1. A novel V2G charging station system based on an edge computing platform and a charging method thereof are characterized by comprising four layers of systems:
charging pile group system: collecting charging and discharging operation information of the electric automobile, simultaneously sending the charging and discharging operation information to an edge internet of things agent calculation platform of a pile group dispatching control system and a charging operation platform of a charging dispatching management control and operation system, and receiving and executing a charging and discharging instruction of a charging pile connected with the electric automobile and issued by a superior system;
pile group scheduling control system: uploading the running state information and the control strategy information of the pile group to an upper charging dispatching management control general platform, receiving the charging and discharging running information of the electric vehicle of a lower charging pile group system, and formulating a running strategy to be sent to each lower charging pile to be executed by combining the requirements issued by the upper charging dispatching management control general platform;
charging scheduling management control and operation system: the system is composed of two physically separated subsystems of a charging dispatching management control main platform and a charging operation platform, information mutual transmission and intercommunication is realized between the subsystems in a wired or wireless network mode, the charging dispatching management control main platform receives electrical state data of an intelligent terminal of a power grid platform area, user demand information of the charging operation platform, pile group operation state information and control strategy information of a pile group dispatching control system and power grid dispatching requirement information of a superior power grid dispatching control system, an operation strategy is formulated and sent to a subordinate pile group as an execution reference, the charging operation platform receives charging order information and charging discount/subsidy behavior information to calculate charging discount/subsidy, charges are settled to inform a user to execute settlement, charging demand information of a charging application end of the user is received and sent to the charging dispatching management control main platform, and charging scheme information of the charging dispatching management control main platform is received, sending the information to a user charging application terminal so that a user can know the information;
the power grid dispatching control system comprises: receiving regional charging operation information of a charging scheduling management control overall platform, and sending cooperative scheduling information, such as demand response, platform load prediction and scheduling response strategies.
2. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein: the range of the power grid platform area is a single power distribution network area with 110kV, 10kV and 380V voltage levels.
3. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein the charging scheme information includes the following steps:
1) the user records the target SOC value of the current charging as the SOC through manual input or preset in the user charging application terminal1；
2) The charging times for the three charging schemes were estimated, respectively: firstly, ordinary charging, namely starting charging immediately to charge the electric automobile until the power battery is fully charged and the charging service is stopped; secondly, off-peak charging, namely based on common charging, if the peak power price of the power grid is experienced during the charging period, the charging is temporarily stopped until the charging service is stopped because the power battery is fully charged during the off-peak power price period; thirdly, economic charging, namely, the electric automobile feeds power to the power grid to a set allowable discharging depth in the peak electricity price period in the charging period and recharges the power to the target SOC of a user;
3) estimating charge discount amounts of the three charging schemes;
4) pushing estimation results of the three charging schemes to a user charging application terminal;
5) a user selects a charging scheme;
6) if the user participates in the V2G response, an energy management scheduling method of the V2G charging station is called to generate a charging plan, and if the user does not participate in the V2G response, the charging plan is generated according to the charging scheme selected by the user.
7) According to the scheduling control quantity Pev-opt(i,j)A charging plan is executed.
8) And the corresponding charging equipment responds to the charging plan instruction.
9) And after a certain interval time after the response of the last step, if the charging of the electric automobile connected with the charging equipment is completed, ending the charging function of the corresponding equipment and submitting the charging function to a user for settlement, and if the charging is still completed, determining that the charging plan is not completed, and entering the next step.
10) Judging whether the charging plan parameters in the station are changed or not, and returning to execute the steps 6) -8) when the charging plan parameters are changed; and when the charging time is not changed, the current charging plan is continuously executed, and the parameters of the charging plan comprise the changing of the off-site time of the user, emergency stop of charging due to reasons and a power grid dispatching command.
4. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 3, wherein: the charging plan of the step 6) comprises the following steps:
1) establishing a power grid side demand response model of the V2G charging station, wherein the power grid side demand response model comprises the following steps:
a) the station participates in the predicted effect of the power grid side demand response:
Figure FDA0002856219620000031
wherein the content of the first and second substances,
n is the total number of the electric automobiles;
g1the proportion of electric vehicles which can participate in the V2G response scheduling strategy;
N1the specific number corresponding thereto;
g2electric vehicle occupancy for not participating in V2G response scheduling policyRatio, g2＝1-g1；
N2The specific number corresponding thereto;
Pev(i,j)generating charging power for the j time window of the ith electric vehicle;
Pchs(j)charging station load for the desired V2G for the grid for the j time window;
b) and (3) the yield of the station participating in the power grid side demand response:
Figure FDA0002856219620000032
wherein the content of the first and second substances,
λ(PDR) The efficiency function of the V2G charging station for reducing load peak-valley difference is shown, and the effect of the station on the power grid side demand response is reflected in a profit mode;
Pr0awarding a price for the charging station by reducing the load peak to valley difference for a time window of j V2G, the prize price being negative;
t is the number of time windows, and T is 24/delta T;
2) the V2G charging station operation income model comprises:
Figure FDA0002856219620000041
wherein the content of the first and second substances,
Pr1(j)the electricity purchasing price or the electricity selling price of the charging station is negative and the electricity selling price is positive in the j time window;
Pr2(j)the charging or discharging electricity price of the electric automobile in the j time window is negative, and the discharging electricity price is positive;
Pev(i,j)the charging is positive and the discharging is negative for the operation power of the ith charging pile in the j time window;
Δ t represents a scheduling time window;
3) the V2G charging station integrated revenue model, the integrated revenue model comprising:
FS＝a0f0+a1f1；
wherein the content of the first and second substances,
a0、a1weighting factors, a, for the demand response returns and V2G station returns of a station, respectively0+a1＝1；
4) Establishing a V2G user revenue model, wherein the user revenue model comprises:
a) the charging expenditure of the user electric automobile is as follows:
Figure FDA0002856219620000042
b) psychological patch f for depreciation of power battery of user electric automobile caused by non-trip discharge behaviorC1Comprises the following steps:
when P is presentev(i,j)>At 0, fC1＝0；
When P is presentev(i,j)<At the time of 0, the number of the first,
Figure FDA0002856219620000043
wherein the content of the first and second substances,
beta is depreciation subsidy price coefficient of battery discharge and is a negative value;
c) the cost of integrating the charge/discharge behavior of the V2G user is:
FC＝fC0+fC1；
5) V2G charging station energy management scheduling optimization objective, the scheduling optimization objective comprising:
F∈max FS∩minFC；
when the dual targets of maximizing the income of the V2G charging station and minimizing the charging expense of the user can be simultaneously met, the charging/discharging power P of the ith electric vehicle j time windowev-opt(i,j)Is a scheduling control quantity that can translate the energy management scheduling optimization objective with respect to satisfying a binary variable FSAnd FCSingle target of minimum value of:
minF＝(-FS,FC)T。
5. the edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein: the pile group dispatching control system belongs to any one or more of charging pile types of alternating current charging pile/direct current charging pile/V2G charging pile/charging arch/automatic charging equipment.
6. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein: the dispatching management control system of the charging station is used as a dispatching management controller of the charging station or a regional charging station and manages a plurality of edge internet of things agent computing platforms.
7. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein: the dispatching management control system of the charging station is composed of a plurality of charging pile group systems and a plurality of sub-pile group dispatching control systems formed by respective edge internet of things agent computing platforms, and the dispatching management control systems which are uniformly connected to the charging station are controlled.
8. The edge computing platform-based novel V2G charging station system and the charging method thereof according to claim 1, wherein: the form of the user charging application end comprises a mobile phone APP, a charging pile touch screen, voice recognition software and hardware and intelligent home equipment, and is directly or indirectly connected to a charging operation platform through a physical communication means to realize data interaction, wherein the physical communication means comprises an Ethernet, 3G \4G \5G wireless communication and a local area network.
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