CN111740403A - Master-slave game scheduling strategy for power grid operator and electric vehicle cluster - Google Patents

Master-slave game scheduling strategy for power grid operator and electric vehicle cluster Download PDF

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CN111740403A
CN111740403A CN202010389806.XA CN202010389806A CN111740403A CN 111740403 A CN111740403 A CN 111740403A CN 202010389806 A CN202010389806 A CN 202010389806A CN 111740403 A CN111740403 A CN 111740403A
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charging
electric
electric vehicle
platform
power grid
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CN111740403B (en
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高强
周晨
应国德
朱逸芝
余剑锋
唐琦雯
杨强
孙思扬
赵莉
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Zhejiang University ZJU
Taizhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Zhejiang University ZJU
Taizhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • B60L53/30—Constructional details of charging stations
    • B60L53/31—Charging columns specially adapted for electric vehicles
    • 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
    • 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
    • B60L53/63—Monitoring or controlling charging stations in response to network capacity
    • 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
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • 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
    • B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • 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
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • 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
    • Y02T90/12—Electric charging stations

Abstract

Aiming at the defects and shortcomings of the prior art, the invention not only promotes the V2G technology, but also ensures the stability of the whole power grid under the regulation and control configuration of V2G, and also considers the rights and interests of users of ordinary electric vehicles, and reduces the loss of batteries. A master-slave game scheduling strategy for a power grid operator and an electric vehicle cluster is characterized in that electric vehicle users form a cluster, the goal of minimizing the total charging cost is taken, and the Starkelberg balance is finally achieved after multiple games. By adopting the technical scheme, the reasonable charging and discharging strategy is formulated by utilizing the characteristic that the electric automobile can be charged and discharged, so that the electric automobile meets the charging requirement, and simultaneously realizes the effect of helping the peak clipping and valley filling of the power grid together with the energy storage equipment, and the power grid operator and the electric automobile user can obtain better economic benefits. Especially, the rights and interests of the electric automobile user are guaranteed.

Description

Master-slave game scheduling strategy for power grid operator and electric vehicle cluster
Technical Field
The invention relates to the technical field of electric automobiles, in particular to a method for charging and scheduling an electric automobile.
Background
With the rapid development of economy, the problems of resource shortage and environmental pollution become more and more serious. The electric automobile is becoming the main development direction of the automobile industry because of its energy-saving and environment-friendly characteristics. With the national policy support and the active participation of various large automobile manufacturers, the technology level of electric automobiles is increasing day by day. But the current huge automobile market is intensifying the resource consumption, and simultaneously, the urban energy sources are added with more pressure. In the process, the charging of the electric automobile becomes an important load borne by the power grid, but the electric automobile can also be used as a power supply to feed back to the power grid, so that the peak clipping and valley filling of the power grid are facilitated. Against this background, the charging and discharging behaviors of the electric vehicle need to be reasonably scheduled. For this, the patent numbers in the prior art are: the invention patent CN201510767620.2 discloses an electric vehicle power distribution scheduling control method based on V2G technology, which considers the influence of electric vehicle charging and discharging power, considers the capacity of a power distribution network, the technical conditions of the electric vehicle and other limiting factors, further considers the traffic factors of the electric vehicle such as vehicle driving routes, charging/discharging access and the like, comprehensively determines the optimal charging and discharging scheduling strategy of the electric vehicle which is more in line with the reality, and controls the charging and discharging of the electric vehicle by utilizing a V2G system to realize the power distribution scheduling control of the electric vehicle; the embodiment and related data show that the electric vehicle power distribution scheduling control method based on the V2G technology can effectively improve negative effects brought to system reliability by large-scale electric vehicle access, improve the load utilization rate of a power distribution network, reduce the load peak-valley difference of the power distribution network, and help to improve the economy of electric vehicle power distribution scheduling and power distribution network operation.
However, most of the V2G technologies in the prior art are planned from the perspective of the power grid, and users cannot freely choose to use electric vehicles in the process. Forced use of an electric vehicle not only results in grid fluctuations, but may also cause damage to the batteries of the electric vehicle.
Disclosure of Invention
Aiming at the defects and shortcomings of the prior art, the invention not only promotes the V2G technology, but also ensures the stability of the whole power grid under the regulation and control configuration of V2G, and also considers the rights and interests of users of ordinary electric vehicles, and reduces the loss of batteries.
A master-slave game scheduling strategy for a power grid operator and an electric vehicle cluster is characterized in that electric vehicle users form a cluster, the total charging cost of the electric vehicle cluster is calculated, and the power grid operator estimates the power grid base load P of the same dayBD(t) and distributed Power Source PDG(t) after applying force, calculating the charge-discharge strategy P of energy storage in the same dayES(t) and informing the electric automobile cluster that the electric automobile cluster meets various constraint conditionsOn the premise of minimizing the total charging cost, the electric vehicle cluster total charging and discharging strategy formed by the optimal charging and discharging strategy of each electric vehicle is determined
Figure RE-GDA0002652551380000021
And reporting to the electric network operator; optimal charging and discharging strategy for readjusting stored energy by power grid operator
Figure RE-GDA0002652551380000022
And the cluster of the electric automobiles is informed again; after multiple games, the Stark-Berger equilibrium is finally achieved.
When the power grid calculates the charging and discharging strategy of the energy storage in the day, the payment function U is reduced as far as possible, namely the requirement of energy storage in the day is met
Figure RE-GDA0002652551380000023
Wherein t is an integer, is more than or equal to 1 and less than or equal to 24 and is 24 hours in a day; the constraint condition is
Figure RE-GDA0002652551380000024
Wherein, Pmin,PmaxIs the minimum and maximum capacity of the energy storage device; SoC (system on chip)0Is the initial amount of energy stored; Δ t is the length of the unit time interval;
Figure RE-GDA0002652551380000025
is the maximum charge-discharge power of stored energy.
Preferably, the calculation mode of the electric vehicle cluster total charge and discharge strategy is as follows:
Figure RE-GDA0002652551380000026
the constraint condition is
Figure RE-GDA0002652551380000027
-Pnch≤xi,t≤Pnch、
Figure RE-GDA0002652551380000028
Wherein n is the total number of the electric automobiles, ts.i、te,i、Pch,iRespectively, charging start time, end time, and total charging demand, x, of the ith vehiclei,tIs the charging and discharging strategy of the ith electric vehicle at time t, xi,t> 0 represents the selective charging of the electric automobile, xi,t< 0 represents the electric vehicle selective discharge, x i,t0 represents that the electric automobile selects not to carry out charging and discharging behaviors, and xi,tAnd PEV(t) a relationship of
Figure RE-GDA0002652551380000031
Wherein x is-i,tIs the sum of loads corresponding to the charging and discharging strategies of other electric vehicles except the ith electric vehicle at the time t, PmaxAnd PminIs the minimum and maximum electric quantity of the battery of the electric automobile, SoC0,iIs the initial battery charge of the ith electric vehicle, PnchIs the maximum rated power of charging and discharging of the electric automobile, cne,iIs the total charge for the ith electric vehicle in the non-cooperative game.
Preferably, the electric vehicles connected to the charging pile are classified, and the electric vehicles are classified into the electric vehicle with high charging pause frequency and the electric vehicle with low charging pause frequency according to the use frequency of the electric vehicles in the charging time period, and the electric vehicles are respectively arranged in different electric vehicle clusters. The configuration is performed by giving priority to an electric vehicle having a low charge pause frequency, thereby reducing the influence on the electric vehicle battery.
Preferably, the electric automobile with high charging pause frequency does not add game scheduling. It should be noted that, since the usage conditions of the vehicle owners are different in different time periods, different vehicle charging suspension frequencies change with time.
The invention also comprises a charging pile platform which is formed by combining a charging pile access platform, a demand response platform and an operator platform; wherein:
the charging pile access platform is connected with a specific charging pile and manages the accessed charging pile;
the demand response platform makes and releases a demand response plan;
the operator platform directly faces the electric vehicle user for interaction.
Preferably, the operator platform and the charging pile access platform share charging pile data and interact with each other to control the data.
Preferably, the interaction of the demand response data is performed between the operator platform and the demand response platform.
Preferably, the interaction of the operator platform includes user management, charging pile reservation, charging and recharging, billing and participation in a demand response plan.
The invention also comprises a charging pile which is connected in the charging pile platform and used as an interface for connecting the electric automobile to the charging pile platform, collects the information of the connected electric automobile and executes the charging strategy of the charging pile platform.
By adopting the technical scheme, the reasonable charging and discharging strategy is formulated by utilizing the characteristic that the electric automobile can be charged and discharged, so that the electric automobile meets the charging requirement, and simultaneously realizes the effect of helping the peak clipping and valley filling of the power grid together with the energy storage equipment, and the power grid operator and the electric automobile user can obtain better economic benefits. Especially, the rights and interests of the electric automobile user are guaranteed.
Drawings
FIG. 1: a schematic diagram of a starkeberg master-slave game model of the electric vehicle V2G;
FIG. 2: a typical daily graph of the basic load and the distributed power output;
FIG. 3: an energy storage and electric vehicle cluster charging and discharging optimal strategy curve chart of a power grid operator;
Detailed Description
The present invention will be described in further detail with reference to examples for the purpose of facilitating understanding and practice of the invention by those of ordinary skill in the art, and it is to be understood that the present invention has been described in the illustrative embodiments and is not to be construed as limited thereto.
In the practical application process, the electric automobile not only is a simple power load, but also can be regarded as a distributed energy storage and power supply with controllable charging and discharging behaviors, so that the electric automobile is used as an energy storage unit to be charged in the off-peak period of the power Grid load, the redundant electric quantity of the power Grid is stored, and the electric automobile is used as a power supply to reversely feed electric energy to the power Grid in the peak period of the power Grid load, so that the electric energy is changed from 'load' to 'source', namely V2G (Vehicle to Grid). The reasonable electric automobile V2G scheduling strategy can not only solve the negative influence of large-scale electric automobile unordered charging on the power grid, but also provide various auxiliary services such as frequency modulation peak shaving and rotary standby for the power grid, thereby greatly reducing the charging cost of users and the operating cost of the power grid, improving the load curve and the power quality of the power grid, improving the utilization efficiency of a distributed renewable power supply and the like. Therefore, how to make a reasonable electric vehicle V2G strategy to enable the electric vehicle to better provide auxiliary service for the power grid on the premise of meeting the charging requirement of the electric vehicle and considering the uncertainty of the distributed power supply output becomes a very important problem.
In addition, electric vehicles have also shown great advantages in providing ancillary services to the power grid. The electric automobile often stops at home for more than 12 hours at night, and the time from empty power to full power is generally 6-8 hours. If the electric vehicle can be reasonably scheduled to be charged in the off-peak period of the traditional load of the power grid on the premise of ensuring the charging requirement of the electric vehicle, and the electric vehicle is used as a power supply to be discharged in the peak period of the traditional load of the power grid, the negative influence of the disordered charging of the electric vehicle on the power grid can be relieved, the peak-valley difference of the load of the power grid can be improved, the frequency modulation and peak shaving cost of the power grid can be saved, more electric energy generated by a distributed power supply can be consumed, the utilization rate of renewable energy sources can be improved, and the advantages of energy conservation and environmental protection of the electric vehicle can be.
Compared with the conventional charging mode with a large margin on a time scale, the charging mode is not suitable for the V2G on a space scale because the electric vehicle firstly needs to meet the travel requirement of the user, and the user often does not want to sacrifice the travel convenience of the user and drives the electric vehicle to a node far away for discharging. Meanwhile, the rapid charging of the electric vehicle is not suitable for the V2G, because when the rapid charging occurs, the battery capacity of the electric vehicle is often very low, and the electric vehicle cannot be used as a power supply to reversely deliver electric energy to a power grid. Therefore, the invention only considers that the conventional charging mode of the electric automobile provides the peak shaving auxiliary service to the power grid through the V2G on a time scale, and simultaneously, the charging sequence of the electric automobile can be controlled in time when the charging is carried out in the conventional charging mode, namely, when the charging is carried out for a long time in a residential area or a parking lot at night. The hardware that involves mainly includes electric automobile fills electric pile, remote monitoring platform, the management platform that charges.
As shown in fig. 1:
the method comprises the step (1) of setting the electricity price on the power distribution node as rho (t) a + b (P)BD(t)-PDG(t)+PEV(t)+PES(t)), where ρ (t) is the dynamic electricity price at time t; a and b are the reference electricity price and electricity price multiplying power determined by the power grid operator, wherein a is more than or equal to 0, and b is more than or equal to 0; pBD(t)、PDG(t) and PEV(t) is the conventional load, the distributed power output, and the total charging load of the electric vehicle at time t, respectively, and PEV(t) > 0 represents that the electric vehicle is charging, PEV(t) < 0 represents that the electric vehicle is discharging; pES(t) is the charging and discharging power of the energy storage device, P is the charging and discharging power of the energy storage device when the energy storage device is chargedES(t) > 0; when the stored energy is discharged, PES(t)＜0；
Step (2), the goal of the grid operator is to hopefully minimize the peak shaver cost of the energy storage device during the day, so that the payment function U can be minimized, i.e. satisfied
Figure RE-GDA0002652551380000061
Wherein t is an integer, is more than or equal to 1 and less than or equal to 24 and is 24 hours in a day; the constraint condition is
Figure RE-GDA0002652551380000062
Figure RE-GDA0002652551380000063
Wherein, Pmin,PmaxIs the minimum and maximum capacity of the energy storage device; SoC (system on chip)0Is the initial amount of energy stored; Δ t is the length of the unit time interval;
Figure RE-GDA0002652551380000064
is the maximum charge-discharge power of the stored energy;
and (3) all electric vehicle users play games with the power grid by forming a cluster, wherein the aim of the electric vehicle cluster is to minimize the total charging cost of all electric vehicles participating in cooperation, namely
Figure RE-GDA0002652551380000065
The constraint condition is
Figure RE-GDA0002652551380000066
-Pnch≤xi,t≤Pnch、
Figure RE-GDA0002652551380000067
Wherein n is the total number of the electric automobiles, ts.i、te,i、 Pch,iRespectively, charging start time, end time, and total charging demand, x, of the ith vehiclei,tIs the charging and discharging strategy of the ith electric vehicle at time t, xi,t> 0 represents the selective charging of the electric automobile, xi,t< 0 represents the electric vehicle selective discharge, x i,t0 represents that the electric automobile selects not to carry out charging and discharging behaviors, and xi,tAnd PEV(t) a relationship of
Figure RE-GDA0002652551380000068
Wherein x is-i,tIs the sum of loads corresponding to the charging and discharging strategies of other electric vehicles except the ith electric vehicle at the time t, PmaxAnd PminIs the minimum and maximum electric quantity of the battery of the electric automobile, SoC0,iIs the initial battery charge of the ith electric vehicle, PnchIs the maximum rated power of charging and discharging of the electric automobile, cne,iIs the total charging cost of the ith electric automobile in the non-cooperative game;
step (4), the electric network operator estimatesElectric network base load P of the same dayBD(t) and distributed power supply output PDGAfter (t), firstly, a charge-discharge strategy P for energy storage is formulatedES(t), and informing the electric automobile cluster;
and (5) determining the electric vehicle cluster total charge and discharge strategy consisting of the optimal charge and discharge strategies of each electric vehicle by taking the minimized total charge cost as the target on the premise that the electric vehicle cluster meets various constraint conditions
Figure RE-GDA0002652551380000071
And reporting to the electric network operator;
step (6), the electric network operator re-determines the optimal charging and discharging strategy of the stored energy
Figure RE-GDA0002652551380000072
And the cluster of the electric automobiles is informed again;
and (7) after multiple games are played in the steps (4) to (6), the Starkelberg equilibrium is finally achieved, and the strategy is the energy storage optimal strategy of the power grid operator and the electric vehicle charging and discharging optimal strategy of the electric vehicle aggregator.
In order to achieve the purpose of the invention, a charging pile platform is also needed, which is formed by combining a charging pile access platform, a demand response platform and an operator platform; the charging pile access platform is connected with a specific charging pile and manages the accessed charging pile; the demand response platform makes and releases a demand response plan; the operator platform directly faces the electric vehicle user for interaction. The operator platform and the charging pile access platform share charging pile data and mutually interact control data. And the operator platform and the demand response platform carry out interaction of demand response data. The interaction of the operator platform comprises user management, charging pile reservation, charging and recharging, charging and participation in a demand response plan.
One of them kind fills electric pile, is connected to the interface that fills the electric pile platform as with electric automobile, collects the electric automobile information who connects, carries out the strategy of charging that fills the electric pile platform simultaneously.
As shown in fig. 2 and fig. 3, it is assumed that an electric car parking lot is located in a commercial office building, and the electric car V2G responsible for the distribution node is scheduled in the daytime. The parking lot has 150 electric vehicles, the charging power of each electric vehicle can be changed within +/-100 kW, the distribution of arrival and departure time of the electric vehicles accords with automobile travel survey data, and the electric quantity of a battery at the arrival time can be calculated by an electric vehicle hidden Markov model; the power distribution node is also connected with a distributed power supply consisting of a roof photovoltaic and a small fan, the power distribution node is divided into 24 time intervals in one day, and a charging and discharging strategy in the hour is determined when each interval starts; the parameters are set to a ═ 20 and b ═ 0.1 ($).
The following electric vehicle charging and discharging strategies are subjected to analog simulation and comparative analysis.
(1) And (4) disordered charging.
If all electric vehicles adopt the unordered charging strategy, namely, the electric vehicles start to be charged immediately when arriving at the parking lot, and keep the parking state after the charging is finished without discharging. Under the strategy, the charging load of the electric automobile does not help the power distribution network to carry out peak clipping and valley filling, but increases the peak-valley difference of the system, prolongs the duration of the peak value of the load of the system, and is very unfavorable for the safe and economic operation of the power distribution network. Meanwhile, the total charging cost of the electric vehicle user reaches 120.98 $.
(2) And (4) disordered charge and discharge.
Considering that each electric automobile is charged and discharged, on the premise of meeting respective charging requirements, the electric automobiles select to discharge in a proper time period, and earn the maximum benefit to the electric automobiles, so that the charging cost is reduced as much as possible. However, it is assumed that each electric vehicle has no information exchange with each other, i.e. acts completely according to its own optimal strategy, and does not consider the strategies of other electric vehicles. All electric vehicles will choose to discharge during peak periods of the system's original load (i.e., about 9:00-13:00) and charge during valley periods of the system's original load (i.e., about 14:00-18:00), thereby reducing peak-to-valley differences at the distribution nodes to some extent, increasing the utilization efficiency of new energy, and reducing the total charging cost of the electric vehicle to 61.95 $.
However, it should be noted that 7:00-9:00 and 14:00-18:00 become new load peaks for the distribution nodes. If more electric vehicles adopt the strategy to charge and discharge, the loads in the two time periods are further increased, so that the charging cost of the electric vehicles is not reduced or increased, the load fluctuation is more severe, and potential risks are brought to the safe and stable operation of the power distribution network. Therefore, it is necessary to perform coordinated scheduling of the charging and discharging behaviors of each electric vehicle.
(3) The Starkeberg primary-secondary game adopts the technical scheme of the invention.
Assuming that the maximum charge/discharge power of the energy storage device of the grid operator is 10MW, the energy storage device of the grid operator can earn 27.75$ a day and the total charge cost of the electric vehicle is 13.91$ when both parties reach starkeberg balance. It can be found that after the energy storage device of the grid operator is connected to the peak shaving service, the charging cost of the electric vehicle cluster is increased, but still much less than the cost of the unordered charging and discharging.
Meanwhile, it should be noted that, since the electric vehicle leaves the parking lot of the commercial office building after the night, the electric network operator cannot perform peak clipping and valley filling on the load of the power distribution network at night through the V2G behavior of the electric vehicle. After the energy storage equipment of a power grid operator is considered, certain peak regulation service can be carried out all day long, and the fluctuation of node load is relieved better. In this regard, we divide electric vehicles into an electric vehicle with a high charging suspension frequency and an electric vehicle with a low charging suspension frequency according to the usage frequency of the electric vehicle in the charging period, and the electric vehicles and the charging suspension frequency are respectively arranged in different electric vehicle clusters. And this frequency is adjusted as a function of time.
For example, a car owner needs to go out and pay after going home every night. Then on monday-friday, the use frequency thereof at night is high, and the electric vehicle is set in the electric vehicle cluster having a high charging pause frequency. And when the user has a rest at home on weekends, the user does not go out at night, and the user is adjusted to the electric automobile cluster with low charging pause frequency.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.

Claims (10)

1. A master-slave game scheduling method for power grid operators and electric vehicle clusters is characterized in that: electric vehicle users form a cluster, the total charging cost of the electric vehicle cluster is calculated, and a power grid operator estimates the power grid base load P of the same dayBD(t) and distributed Power Source PDG(t) after applying force, calculating the charge-discharge strategy P of energy storage in the same dayES(t) informing the electric automobile cluster, and determining the electric automobile cluster total charge and discharge strategy formed by the optimal charge and discharge strategy of each electric automobile by the electric automobile cluster with the aim of minimizing the total charge cost on the premise of meeting various constraint conditions
Figure FDA0002483598740000011
And reporting to the electric network operator; optimal charging and discharging strategy for readjusting stored energy by power grid operator
Figure FDA0002483598740000012
And the cluster of the electric automobiles is informed again; after multiple games, the Stark-Berger equilibrium is finally achieved.
2. The method for dispatching the electric vehicle cluster to the power grid operation according to claim 1, wherein the method comprises the following steps: when the power grid calculates the charging and discharging strategy of the energy storage in the day, the payment function U is reduced as far as possible, namely the requirement of energy storage in the day is met
Figure FDA0002483598740000013
Wherein t is an integer, is more than or equal to 1 and less than or equal to 24 and is 24 hours in a day; the constraint condition is
Figure FDA0002483598740000014
Figure FDA0002483598740000015
Wherein, Pmin,PmaxIs the minimum and maximum capacity of the energy storage device; SoC (system on chip)0Is the initial amount of energy stored; Δ t is the length of the unit time interval;
Figure FDA0002483598740000016
is the maximum charge-discharge power of stored energy.
3. The method for dispatching the electric vehicle cluster for the power grid operation according to claim 1 or 2, wherein the calculation mode of the total charging and discharging strategy of the electric vehicle cluster is as follows:
Figure FDA0002483598740000017
the constraint condition is
Figure FDA0002483598740000018
Figure FDA0002483598740000019
-Pnch≤xi,t≤Pnch、
Figure FDA00024835987400000110
Wherein n is the total number of the electric automobiles, ts.i、te,i、Pch,iRespectively, charging start time, end time, and total charging demand, x, of the ith vehiclei,tIs the charging and discharging strategy of the ith electric vehicle at time t, xi,t> 0 represents the selective charging of the electric automobile, xi,t< 0 represents the electric vehicle selective discharge, xi,t0 represents that the electric automobile selects not to carry out charging and discharging behaviors, and xi,tAnd PEV(t) a relationship of
Figure FDA0002483598740000021
Wherein x is-i,tIs the sum of loads corresponding to the charging and discharging strategies of other electric vehicles except the ith electric vehicle at the time t, PmaxAnd PminIs the minimum and maximum electric quantity of the battery of the electric automobile, SoC0,iIs the initial battery charge of the ith electric vehicle, PnchIs the maximum rated power of charging and discharging of the electric automobile, cne,iIs the total charge for the ith electric vehicle in the non-cooperative game.
4. The method as claimed in claim 1, wherein the electric vehicles connected to the charging piles are classified into electric vehicles with high charging suspension frequency and electric vehicles with low charging suspension frequency according to the use frequency of the electric vehicles in the charging time period, and the electric vehicles are respectively arranged in different electric vehicle clusters.
5. The method for dispatching the electric vehicle cluster for the power grid operation is characterized in that the electric vehicles with high charging pause frequency are not added with game dispatching.
6. A charging pile platform is characterized by being formed by combining a charging pile access platform, a demand response platform and an operator platform; wherein:
the charging pile access platform is connected with a specific charging pile and manages the accessed charging pile;
the demand response platform makes and releases a demand response plan according to the method of claim 1;
the operator platform directly faces the electric vehicle user for interaction.
7. The charging pile platform of claim 6, wherein the operator platform and the charging pile access platform share charging pile data and interact with each other to control data.
8. The charging pile platform of claim 6, wherein the interaction of demand response data is performed between an operator platform and a demand response platform.
9. The charging pile platform of any one of claims 6-8, wherein the operator platform interactions include customer management, charging pile reservations, charging charges, billing, and participation in demand response programs.
10. A charging pile characterized by being connected in the charging pile platform of claim 6, and as an interface for connecting an electric vehicle to the charging pile platform, collecting information on the connected electric vehicle while executing a charging policy of the charging pile platform.
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