CN107069753A - A kind of electric automobile of consideration behavior randomness participates in power grid voltage regulating dispatching method - Google Patents
A kind of electric automobile of consideration behavior randomness participates in power grid voltage regulating dispatching method Download PDFInfo
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- CN107069753A CN107069753A CN201710341333.4A CN201710341333A CN107069753A CN 107069753 A CN107069753 A CN 107069753A CN 201710341333 A CN201710341333 A CN 201710341333A CN 107069753 A CN107069753 A CN 107069753A
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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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
- B60L53/63—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
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/16—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
-
- 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]
-
- 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
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/62—The condition being non-electrical, e.g. temperature
- H02J2310/64—The condition being economic, e.g. tariff based load management
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- 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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/30—Reactive power compensation
-
- 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
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- 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
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- 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
-
- 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
- Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
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- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
-
- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
- Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
- Y04S30/12—Remote or cooperative charging
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- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
- Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
- Y04S30/14—Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
Power grid voltage regulating dispatching method is participated in the invention discloses a kind of electric automobile of consideration behavior randomness, take into full account automobile user behavior randomness, meeting Network Voltage Stability, under charging electric vehicle demand and electric automobile charging station maximization of economic benefit, by the Reactive Power Price mechanism for devising a kind of equalizaing charge station and automobile user both sides' economic benefit, realize the rational management to networking electric automobile, so as to effectively improve the stability of line voltage, greatly improve the economic well-being of workers and staff of electric automobile charging station, and the financial expenditure of automobile user can be substantially reduced.
Description
Technical field
The invention belongs to electric vehicle engineering field, more specifically, it is related to a kind of the electronic of consideration behavior randomness
Automobile participates in power grid voltage regulating dispatching method.
Background technology
Because fossil fuel is in short supply, environmental pollution the problems such as it is increasingly serious, use the electric automobile of renewable and clean energy resource
Increasingly it is widely applied.Substantial amounts of charging electric vehicle will bring the load rapid growth of a new round, and this is negative to electricity consumption
For the power system that lotus peak-valley difference is increasingly increased, huge power supply pressure is added.
V2G (Vehicle-to-grid) technology refers to that pair of energy and information can be carried out between electric automobile and power network
To flowing.In such a mode, electric automobile has been not only the power load of power network, also become the power supply source of power network to
Power network feeds or is used as the energy storage device of power network.Meanwhile, the time that electric automobile had more than 80% in one day is in the free time
State.It therefore, it can provide the assistant services such as frequency modulation, pressure regulation, spinning reserve using electric automobile for power network.
At present, the dispatching method of power grid voltage regulating is participated in for electric automobile, a certain degree of grind has been expanded both at home and abroad
Study carefully, but be still in the junior stage, need to be studied.Periodical《Electric power network technique》2nd phase " the reactive power based on V2G in 2013
The text of compensation technique " one is proposed idle for family's load progress as reactive power compensator using electric automobile based on V2G technologies
The control program of local compensation；Periodical《Scientific and technical innovation》" electric automobile reactive-load compensation based on track with zero error of volume 6 in 2017
The text of research " one is controlled by dead-beat control method to electric automobile for the reactive power that microgrid is provided, and realizes idle benefit
Repay, reduce influence of the microgrid to bulk power grid.
In the studies above result, the control method of power grid voltage regulating is participated in for electric automobile, be based on to independent electrical first
Reactive-load compensation is realized in the control of electrical automobile, does not account for the scheduling of many electric automobiles；Secondly lack and automobile user is used
The consideration for the randomness that garage is.But actually separate unit electric automobile is smaller to the strength of adjustment of line voltage, pass through scheduling
It is more efficient that electric automobile group participates in power grid voltage regulating；In addition, the day of automobile user conventional garage is with uncertainty,
The time of each electric automobile access power network and initial quantity of electricity are different, and its minimum satisfaction trip required when leaving
Electricity is also not quite similar.Therefore, current research lacks effective directive significance for practical application.
The content of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of electric automobile of consideration behavior randomness ginseng
With power grid voltage regulating dispatching method, automobile user behavior randomness is taken into full account, Network Voltage Stability, electric automobile is being met
Under charge requirement and electric automobile charging station maximization of economic benefit, the rational management of networking electric automobile is realized.
For achieving the above object, a kind of electric automobile of consideration behavior randomness of the invention participates in power grid voltage regulating scheduling
Method, it is characterised in that comprise the following steps：
(1) the game Competitive Bidding Model of the idle price of electric automobile, is set up
(1.1) the idle price of electric automobile, is calculated：
Wherein,Represent the idle price of electric automobile in h-th of time interval；Represent that electric automobile sells nothing
The base price of work(；mhRepresent the proportionality coefficient of h-th of time interval underexcitation electricity price；Represent in h-th time interval to
The upper limit that power network compensation is idle；Represent idle exert oneself size of n-th electric automobile in h-th of scheduling time inter；N tables
Show the number for the electric automobile for obeying scheduling；
(1.2) the game Competitive Bidding Model of the idle price of electric automobile, is set up
The deviation of optimal compensation amount, leads to needed for reactive-load compensation amount and power network that (1.2.1), calculating charging station are provided for power network
The deviation is crossed to represent voltage regulation result of the charging station to power network；
Wherein, futiThe deviation of OPTIMAL REACTIVE POWER demand needed for the reactive-load compensation amount and power network that are provided for charging station for power network
Function, the smaller then voltage regulation result of deviation is better；Optimal reactive-load compensation amount needed for expression power network；
(1.2.2), calculate the economy return that every automobile user participates in pressure regulation；
Wherein, fEVnThe economy return function that power grid voltage regulating is obtained is participated in by n-th electric automobile；Set s ∈ N { n } table
Show in all electric automobile set for obeying scheduling and remove n-th electric automobile；
(1.2.3), choose optimal voltage regulation result and every automobile user desired maximum of the charging station to power network
Economy return constitutes the game Competitive Bidding Model of the idle price of electric automobile；
(2) Profit model of charging station, is set up；
(2.1), charging station obtains that market is active and Reactive Power Price data at power network；
(2.2) charging electric vehicle retail price, is determined according to market active electricity price, equal to γ times of market active electricity price,
γ>1；
(2.3) the income sum that the income and participation power grid voltage regulating for, obtaining charging electric vehicle are obtained is used as charging station
Total revenue Income, will buy the expense for establishing branch and payment automobile user participation pressure regulation by cable as totle drilling cost Cost from power network,
Set up the Profit model of charging station：
Rev=Income-Cost；
Wherein, st and et represent the whole story of scheduling slot respectively；Scheduling slot is equally divided into multiple time intervals, each
A length of Δ t during time interval；RhRepresent charging electric vehicle retail price in h-th of time interval；γ represents charging station setting
The proportionality coefficient of retail price and power network market price；WithRepresent that active in h-th of time interval and Reactive power marke is electric respectively
Valency；WithRespectively represent n-th electric automobile charged in h-th of time interval consumption active power and injected to power network
Reactive power；
(3) restricted model of line voltage, is set up
According to regulation of the power system to Network Voltage Stability, the restricted model of line voltage is set up：
Vmin≤Vi≤Vmax；
Wherein, VmaxAnd VminThe safe range upper and lower limit of line voltage is represented respectively；ViRepresent power system topological structure
In i-th bus voltage；
(4) power module of electric automobile access point, is set up
(4.1) on-position of the charging station in power network, i.e. electric automobile access point, are determined；
(4.2), using charging electric vehicle as the burden with power of power network, the reactive power that it injects to power network is as power network
Reactive-load compensation, calculates the burden with power of all electric automobiles for obeying scheduling of access point and idle sum of exerting oneself, sets up on power network
The power module of electric automobile access point：
Wherein,WithThe burden with power of electric automobile is represented at i-th bus of power network respectively and idle is exerted oneself；
(5), the maximum for the charging station Profit model set up with step (2) turns to object function, with step (3) and step
(4) the line voltage restricted model and the power module of electric automobile access point set up are constraints, set up charging station pair
The Optimized Operation mathematical modeling of electric automobile；
(6) user behavior randomness, is analyzed, estimation electric automobile reaches/left time and the battery electric quantity shape of charging station
State (SOC)
(6.1) user behavior data, is analyzed, the electric automobile number of charging station is accessed/left to one day each hour of estimation；
(6.1.1) analyzes user behavior data, is fitted by Poisson and obtains in one day reaching for electric automobile at charging station
Rate/departure rate；
(6.1.2), according to it is resulting up to/departure rate calculates every two electric automobiles and continuously reached/leave charging station when
Between be spaced, until all vehicles reached/leave charging station：
Wherein, τ represents that every two electric automobiles continuously reach/left the time interval of charging station；λ represents that electric automobile is arrived
Up to rate/departure rate；ξ is obedience (0,1) equally distributed stochastic variable；
(6.1.3) ,/time departure interval reached according to gained, obtain each electric automobile reach/leave charging station
The specific time；
(6.1.4) counts the electric automobile number for each hour reaching/leaving charging station；
(6.2) user behavior data, is analyzed, passes through initial cells SOC when just too distribution estimation electric automobile reachesinit
With minimum battery SOC required when leavingdes；
(7) the electric automobile relevant parameter, estimated based on step (6) and the basic load, the circuit that are obtained at power network
Impedance, will be divided into multiple scheduling slots scheduling time, the optimization set up using sequential quadratic programming method calculation procedure (5)
Scheduling mathematic model, obtain to each electric automobile in each scheduling slot the charge efficiency of optimum allocation and it is idle exert oneself it is big
It is small, and as dispatch command of the charging station to electric automobile, and send successively to corresponding automobile user, completion was dispatched
Journey.
What the goal of the invention of the present invention was realized in：
A kind of electric automobile of consideration behavior randomness of the present invention participates in power grid voltage regulating dispatching method, takes into full account electronic vapour
Car user behavior randomness, is meeting Network Voltage Stability, charging electric vehicle demand and electric automobile charging station economy effect
Under benefit is maximized, by devising the Reactive Power Price mechanism at a kind of equalizaing charge station and automobile user both sides' economic benefit,
The rational management to networking electric automobile is realized, so as to effectively improve the stability of line voltage, is greatly improved electronic
The economic well-being of workers and staff of vehicle charging station, and the financial expenditure of automobile user can be substantially reduced.
Meanwhile, a kind of electric automobile of consideration behavior randomness of the invention participates in power grid voltage regulating dispatching method also with following
Beneficial effect：
(1), the present invention has taken into full account the randomness that automobile user is with garage, by having estimated that electric automobile reaches
To/the data such as time and SOC of leaving charging station come the scheduling strategy designed, more tally with the actual situation, with more practical guidance
Meaning；
(2), the present invention devises the idle excitation between electric automobile charging station and automobile user based on game theory
Electricity price Bidding Mechanism, realizes equilibrium of both Network Voltage Stability and automobile user economic benefit, more fully
The enthusiasm that electric automobile participates in power grid voltage regulating has been transferred, effectively the charging for reducing automobile user can also have been paid wages；
(3), present invention design scheduling strategy has ensured the economic interests of charging station, also reduces a large amount of electric automobiles grid-connected
Charge the negative effect brought to line voltage, it is significant with the grid-connected problem of electric automobile to solving.
Brief description of the drawings
Fig. 1 is the network system topology diagram of electric automobile access；
Fig. 2 is the game structure chart between electric automobile charging station and automobile user；
Fig. 3 is active/Reactive power marke electricity price curve map in power network one day；
Fig. 4 is power network basic load situation curve map in scheduling time；
Fig. 5 is the probability distribution block diagram and line chart that electric automobile reached/left residence in one day；
Fig. 6 is time interval block diagram between the electric automobile of continuous two return homes in one day；
Fig. 7 is time interval block diagram between the electric automobile that continuous two are left home in one day；
Fig. 8 is electric automobile electricity estimation flow chart；
Fig. 9 is Optimal Operation Model solution procedure flow chart；
Figure 10 is the optimal active power dispatch instruction block diagram of electric automobile；
Figure 11 is the OPTIMAL REACTIVE POWER dispatch command block diagram of electric automobile；
Figure 12 is each busbar voltage situation of change curve of load boom period；
Figure 13 is that power network terminal voltage changes over time curve；
Figure 14 is the average active consumption/idle power curve figure of electric automobile；
Figure 15 is the spending contrast block diagram of each automobile user.
Embodiment
The embodiment to the present invention is described below in conjunction with the accompanying drawings, so as to those skilled in the art preferably
Understand the present invention.Requiring particular attention is that, in the following description, when known function and design detailed description perhaps
When can desalinate the main contents of the present invention, these descriptions will be ignored herein.
Embodiment
Fig. 1 is the network system topology diagram of electric automobile access.
According to intraday loading condition and electric automobile general commuter time, in the present embodiment, a certain house
The charging station in area is chosen for evening 18 for the scheduling time of electric automobile:Morning 6 00 to next day:00, time interval is 1 small
When, electric automobile number is 150.The corresponding topological structure of electric in the residential quarter is as shown in figure 1, include distributed power source, base
8 bus structures of plinth load and electric automobile charging station, its median generatrix 1 is as a reference point, and its magnitude of voltage is that transformer exports electricity
Pressure value 220V.
With reference to Fig. 1, power grid voltage regulating dispatching method is participated in a kind of electric automobile of consideration behavior randomness of the invention
It is described in detail, specifically includes following steps：
S1, the game Competitive Bidding Model for setting up the idle price of electric automobile
S1.1, the calculating idle price of electric automobile：
It is based on selling idle electricity price function, by basic idle price+excitation to calculate the idle price of electric automobile
Electricity price is constituted；
Wherein,Represent the idle price of electric automobile in h-th of time interval；Represent that electric automobile sells nothing
The base price of work(；mhRepresent the proportionality coefficient of h-th of time interval underexcitation electricity price；Represent in h-th time interval to
The upper limit that power network compensation is idle；Represent idle exert oneself size of n-th electric automobile in h-th of scheduling time inter；N tables
Show the number for the electric automobile for obeying scheduling；
Wherein, if idle the exerting oneself beyond the reactive power demand maximum of power network, incentive price of electric automobile offer
It is negative, i.e. the enjoyable idle income of automobile user is relatively low；And in the compensation range, incentive price is just；
S1.2, the game Competitive Bidding Model for setting up the idle price of electric automobile
The major way that S1.2.1, electric automobile participate in line voltage regulation is by idle operation, then reached optimal
The electric automobile that regulating effect can be equivalent to minimize in electric automobile charging station compass of competency provides reactive-load compensation amount and electricity
The deviation of optimal compensation amount needed for net, takes square being turned to econometric function form and representing charging station to power network for the deviation herein
Voltage regulation result；
Wherein, futiThe deviation of OPTIMAL REACTIVE POWER demand needed for the reactive-load compensation amount and power network that are provided for charging station for power network
Function, the smaller then voltage regulation result of deviation is better；Optimal reactive-load compensation amount needed for expression power network；
S1.2.2, while Network Voltage Stability is maintained, the first purpose that charging station formulates the electricity price is to dispatch
The enthusiasm of automobile user, when user's economic interests are maximized, its enthusiasm can also reach maximum.Therefore, herein most
Bigization automobile user provides the economy return of line voltage regulation service.
We calculate the economy return that every automobile user participates in pressure regulation below；
Wherein, fEVnThe economy return function that power grid voltage regulating is obtained is participated in by n-th electric automobile；Set s ∈ N { n } table
Show in all electric automobile set for obeying scheduling and remove n-th electric automobile；
Wherein, the proportionality coefficient m of electricity price is encouragedhComputational methods be：
1) target, is turned to automobile user economy return maximum, the idle expectation of exerting oneself of each electric automobile is calculated
Value
2), using charging station to the optimal voltage regulation result of power network as target, calculate Nash Equilibrium state under each electric automobile
Idle desired value of exerting oneself
3), by step 1) and 2) in idle desired value of exerting oneselfIt is equal, it is determined that the proportionality coefficient m of excitation electricity priceh, such as
Shown in table 2；
Table 1 is the proportionality coefficient m for encouraging electricity pricehTable；
| Period | 1 | 2 | 3 | 4 | 5 | 6 |
| mh | 0.0368 | 0.0795 | 0.1350 | 0.1632 | 0.0757 | 0.0787 |
| Period | 7 | 8 | 9 | 10 | 11 | 12 |
| mh | 0.0654 | 0.0702 | 0.0656 | 0.1022 | 0.0863 | 0.1106 |
Table 1
Totally idle exert oneself determines charging station voltage regulation result for S1.2.3, electric automobile, and influence charging station is to excitation electricity price ratio
The selection of example coefficient, and Reactive Power Price influence the idle of electric automobile is exerted oneself.Therefore, optimal tune of the charging station to power network is chosen
The game that pressure effect and the desired maximum economy return of every automobile user constitute the idle price of electric automobile is bidded mould
Type；As shown in Fig. 2 the game structural relation between electric automobile charging station and automobile user.
S2, the Profit model for setting up charging station；
S2.1, charging station obtain that market is active and Reactive Power Price data at power network, as shown in Figure 3；
S2.2, charging electric vehicle retail price determined according to market active electricity price, equal to γ times of market active electricity price, γ
>1, in the present embodiment, γ=1.5；
On the one hand S2.3, the income Income sources of electric automobile charging station are to provide voltage-regulation auxiliary for power network
The service charge that service is collected, is the product of the idle Reactive Power Price exerted oneself and issued with grid operator；On the other hand it is for electronic vapour
Car provides the power selling income of charging service, is the product of electricity sales amount and sale of electricity electricity price.The sides of expenditure Cost mono- of electric automobile charging station
Face is that electric expenditure is bought at grid operator, is on the other hand to the automobile user payment services expense for obeying scheduling.
Therefore, based on charging station total revenue Income and total expenditure cost Cost, the Profit model of charging station is set up：
Rev=Income-Cost；
Wherein, st and et represent the whole story of scheduling slot respectively；It is the most frequently used for residential block electric automobile in the present embodiment
Charging interval, i.e., from 18:00 to next day 6:00；Scheduling slot is equally divided into multiple time intervals, each time interval duration
For Δ t, value 1 hour；RhRepresent charging electric vehicle retail price in h-th of time interval；γ represents the zero of charging station setting
The proportionality coefficient of price and power network market price；WithActive in h-th of time interval and Reactive power marke electricity price is represented respectively；WithRepresent respectively n-th electric automobile charged in h-th of time interval consumption active power and injected to power network
Reactive power；
S3, the restricted model for setting up line voltage
According to regulation of the power system to Network Voltage Stability, the restricted model of line voltage is set up：
Vmin≤Vi≤Vmax；
Wherein, VmaxAnd VminThe safe range upper and lower limit of line voltage is represented respectively, according to China《Operation of power networks criterion》
Deng the regulation of file, the voltage tolerance value of 220V user is -10%~+the 7% of system nominal voltage；ViRepresent power network system
The voltage of i-th bus in system topological structure；
As shown in Fig. 4 and table 2, charging station obtains the related datas such as power network basic load, line impedance at power network, uses
Tidal current computing method states the relation of power flow in line voltage and power network：
Pi=Pi-1+Pi G-Pi L-Pi E-rili；
Wherein, IiRepresent the electric current of i-th bus；liIt is used for simplified model as intermediate variable；PiAnd QiStream is represented respectively
Go out the active power and reactive power of i-th bus；xiAnd riThe branch road between i-th bus and i+1 bar bus is represented respectively
On inductance and resistance；WithThe active power output and reactive loss of distributed power source at i-th bus of power network are represented respectively；WithThe burden with power in addition to electric automobile and load or burden without work at i-th bus of power network are represented respectively；WithRespectively
Represent at i-th bus of power network the burden with power of electric automobile and idle exert oneself；
Table 2 is network system branch impedance table；
| Branch road (bus-bus) | 1-2 | 2-3 | 3-4 | 4-5 | 5-6 | 6-7 | 7-8 |
| ri | 0.02 | 0.03 | 0.035 | 0.01 | 0.02 | 0.03 | 0.03 |
| xi | 0.06 | 0.09 | 0.11 | 0.03 | 0.06 | 0.09 | 0.08 |
Table 2
S4, the power module for setting up electric automobile access point
S4.1, determine on-position of the charging station in power network, i.e. electric automobile access point；
S4.2, using charging electric vehicle as the burden with power of power network, the reactive power that it injects to power network is as power network
Reactive-load compensation, calculates the burden with power of all electric automobiles for obeying scheduling of access point and idle sum of exerting oneself, sets up on power network
The power module of electric automobile access point：
Wherein,WithThe burden with power of electric automobile is represented at i-th bus of power network respectively and idle is exerted oneself；
In the present embodiment, the access point of charging station is at bus 4, so charging station at bus in addition to bus 4
Power consumption is zero；In addition, the electric automobile in charging station needs to meet following constraints：
1), charging electric vehicle Constraint：
Wherein, CdesRepresent electric automobile minimum institute's subfam. Spiraeoideae in finishing scheduling；CinitRepresent that electric automobile is opened in scheduling
The initial quantity of electricity during beginning, its concrete numerical value is estimated according to user behavior custom；E represents the battery capacity of electric automobile, takes
It is worth for 16.8kWh；The electricity that n-th electric automobile is filled with h-th of scheduling slot is represented, wherein n is represented to obey and adjusted
The electric automobile sequence number of degree, value is 1,2 ..., N.
2), electric car charger is constrained：
Wherein, S represents apparent energy；SmaxMaximum apparent energy is represented, value is 1.44kVA；In addition, in order to reduce tune
Loss of the journey to the batteries of electric automobile life-span is spent, the present invention limits electric automobile in scheduling process without discharge operation,
So to the active operation Constrained of electric automobile：
S5, the maximum for the charging station Profit model set up with step S2 turn to object function, with step S3 and step S4
The line voltage restricted model and the power module of electric automobile access point set up are constraints, set up charging station to electronic
The Optimized Operation mathematical modeling of automobile；
S6, analysis user behavior randomness, estimation electric automobile reach/left time and the battery electric quantity state of charging station
SOC；
The electric automobile number of charging station is accessed/left to S6.1, analysis user behavior data, one day each hour of estimation；
S6.1.1, the behavioral data for analyzing user, are fitted by Poisson and obtain in one day reaching for electric automobile at charging station
To rate/departure rate；
According to available data statistical analysis, it is only that automobile user, which is sequentially ingressed into/left parking lot, within each period
Vertical event, the probability distribution that electric automobile in one day with abstract Poisson process, could can be accessed/left parking lot by its behavior is carried out
Poisson is fitted, and its detailed process being fitted is：
1. gather the 1st period it is continuous many days in the number sample of electric automobile that accesses/leave；
2. the sample data obeys Poisson distribution, therefore Poisson fitting can be used to obtain the parameter lambda in the period1, i.e.,
Arrival rate/departure rate, subscript represents the 1st period；
3. 1., 2., obtain in one day electric automobile at charging station reaches rate/departure rate to repeat step, as shown in Figure 5；
S6.1.2, basis are resulting to leave the time of charging station up to/departure rate calculates every two electric automobiles and continuously reached/
Interval, until all vehicles reached/leave charging station；
The process that each automobile user reached/left residence is separate, so that vehicle arrival time calculates as an example,
The time interval τ that two electric automobiles are continuously reached is separate, and obeys the quantum condition entropy that parameter is λ, and λ represents vehicle
Arrival rate, quantum condition entropy probability density is：P (τ)=λ e-λτ, both sides are taken the logarithm, time interval τ can be solved.
If given stochastic variable ξ obeys (0,1) and is uniformly distributed, then interval of continuous two cars arrival time can be stated
For：
In the present embodiment, can calculate two electric automobiles reach/time departure interval is respectively such as Fig. 6 and Fig. 7 institutes
Show；
S6.1.3 ,/time departure interval reached according to gained, obtain each electric automobile reach/leave charging station
The specific time；
When it is determined that certain electric automobile due in after, the car can be searched by above-mentioned Poisson fitting result and arrived at
The arrival rate at moment, then solves the electric automobile of next arrival and between time between the moment according to above-mentioned formula
Every thereby determine that next electric automobile arrives at the moment, and according to this method, charging station can be first in scheduling time section
Just the arrival time of all electric automobiles is estimated during electric automobile return home, similarly, the time of leaving home can also do according to identical
Method is tried to achieve.
S6.1.4, as shown in table 3, just can so count the electric automobile number for reaching/leaving charging station for each hour
Mesh；
Table 3 is the numerical statement for reaching/leaving electric automobile in scheduling time per hour；
| Period (point-point) | 14-15 | 15-16 | 16-17 | 17-18 | 18-19 | 19-20 | 20-21 | 21-22 | 22-23 | 23-24 |
| Reach vehicle () | 4 | 13 | 23 | 32 | 34 | 22 | 9 | 6 | 3 | 4 |
| Period (point-point) | 4-5 | 5-6 | 6-7 | 7-8 | 8-9 | 9-10 | 10-11 | 11-12 | 12-13 | 13-14 |
| Leave vehicle () | 2 | 10 | 25 | 37 | 32 | 17 | 9 | 7 | 6 | 5 |
Table 3
S6.2, analysis user behavior data, pass through initial cells SOC when just too distribution estimation electric automobile reachesinit
With minimum battery SOC required when leavingdes；
When considering the situation of electric automobile networking, except access/time departure of electric automobile to be analyzed, in addition it is also necessary to point
Analyse electricity randomness during electric automobile access.According to the statistical analysis for historical data, automobile user can be obtained
The dump energy Normal Distribution of residence is returned to, in addition, the charge capacity of every automobile user has to meet it
Minimum electricity needed for trip next time, automobile user trip Minimum requirements electricity also Normal Distribution, it is obeyed just respectively
State distribution N (0.3,0.02) and N (0.7,0.01), to 18:The initial quantity of electricity of electric automobile and next day 6 when 00:00 finishing scheduling
The data handling procedure of the minimum electricity of Shi Suoxu is as shown in Figure 8, it is assumed that electric automobile can be with the time without dispatch command
Charged with invariable power or wait scheduling, then the estimation process of the electric automobile electricity to being carved at the beginning and end of scheduling is as follows：
1) arrival time and the when of leaving of electric automobile, are calculated according to the electric automobile arrival rate and departure rate fitted
Between, the electric automobile that the electric automobile for starting to reach before dispatching cycle is counted respectively and terminates dispatching cycle to leave afterwards is compiled
Number；
2), generation obeys the electric automobile return home dump energy random data of Poisson distribution and leaves Minimum requirements electricity respectively
Random data is measured, the electric automobile for starting dispatching cycle to reach before is calculated and is dispatching initial quantity of electricity SOC when startinginitAnd
Terminate the minimum Expected energy SOC of the electric automobile that leaves afterwards in finishing scheduling dispatching cyclesdes。
S7, the basic load obtained based on the step S6 electric automobile relevant parameters estimated and at power network, circuit resistance
It is anti-, multiple scheduling slots will be divided into scheduling time, adjusted using the sequential quadratic programming method calculation procedure S5 optimizations set up
Spend mathematical modeling, obtain to each electric automobile in each scheduling slot the charge efficiency of optimum allocation and it is idle exert oneself it is big
It is small, and as dispatch command of the charging station to electric automobile, and send successively to corresponding automobile user, completion was dispatched
Journey.
Example
According to table 3, from 18:00 to next day 6:The electric automobile number statistical result reached between 00 in each time interval, can
To find 24:Reached there is no electric automobile after 00, and in the morning 4 points begin with electric automobile and leave, in finishing scheduling
12 are had before to leave, and provide that this 12 vehicles only carry out charging operations.For remaining electric automobile, connect from electric automobile
Enter charging station to start, charging station is as shown in Figure 9 to the scheduling overall process of electric automobile.
First, the related datas such as basic load, line impedance, market guidance are obtained at power network, pass through designed nothing
Work(excitation electricity price bid process calculates idle excitation electricity price proportionality coefficient；Dispatch for the first time from 18:00 starts, and now remembers st=
1, statistics 18:The related charge data of 72 vehicles arrived at before 00, and solving-optimizing scheduling model, are obtained to these electronic vapour
The optimal scheduling instruction of car, is sent to corresponding automobile user and instructs it 18 successively:00-19:In 00 1 hours
Operation；Dispatch for the second time from 19:00 starts, and remembers st=2, the part electric automobile being scheduled at this point for previous hour
For, its initial quantity of electricity is needed plus the charge capacity in previous hour, while gathering the correlation of newly arrived electric automobile
Data, have updated solving-optimizing scheduling model after data, and the optimal scheduling obtained is instructed for indicating electric automobile 19:00-
20:Mode of operation in 00 1 hours；The rest may be inferred, is all arrived at up to 150 electric automobiles, now st=7, the 7th
The optimum instruction of secondary scheduling is the instruction that all electric automobiles for obeying scheduling should be followed in 6 hours next, optimal active and nothing
Work(dispatch command difference is as shown in Figure 10 and Figure 11；Finally, dispatch command is sent to automobile user, completes scheduling electricity
Electrical automobile participates in the process of power grid voltage regulating.
The main purpose that charging station scheduling electric automobile participates in power grid voltage regulating is to improve grid voltage quality, and Figure 12 is illustrated
In network load peak period (18:00-19:00) voltage condition of each bus of power network, by being accessed without electric automobile, electronic vapour
Car accesses but not joined the line voltage state that pressure regulation and electric automobile participated in after pressure regulation in the case of three kinds and contrasted, Ke Yifa
Existing electric automobile can cause the decline of line voltage as the access of pure load, or even cause spread of voltage.But in charging station
Dispatch electric automobile participate in power grid voltage regulating after, line voltage be improved significantly, not only eliminate due to charging electric vehicle
The negative effect brought to line voltage, and the stability of line voltage greatly improved.Figure 12 result is shown simultaneously
Voltage of the terminal voltage generally than other nodes is lower, therefore when analysis voltage changes with time situation, can choose tool
Representational terminal voltage, the curve that it is changed over time is as shown in figure 13.It can also be seen that charging station is adjusted from the figure
Degree electric automobile participates in power grid voltage regulating and good voltage regulation result is respectively provided with whole scheduling slot.
Electric automobile the participation of each period can be as shown in Figure 14 obey electric automobile charging station scheduling electricity
The active consumption of electrical automobile/idle change curve observation of exerting oneself is drawn.In load boom period, the charging load of electric automobile compared with
It is small, it is idle exert oneself it is larger, to improve the line voltage of peak period.
The present invention, can be with effectively save automobile user car except having good regulating effect to electric voltage
Spending.Figure 15 illustrates electric automobile charging station and has the spending situation of each electric automobile in region under its command, including is only filled
Electric (being designated as charge mode) and spending situation while charging in the case of two kinds of participation power grid voltage regulating (being designated as composite mode).
The charging spending average value of all electric automobiles is respectively 30.9530 cents and 19.9061 cents, charge mode in the case of two kinds
Under average spending be about about 1.55 times averagely paid wages under composite mode, i.e., the spending of automobile user under composite mode
Decrease.If being charged because electric automobile is only used as charging load in power network, and other assistant services are not involved in,
Then it needs to pay all charging expenses；And when electric automobile participates in power grid voltage regulating, user can be from electric automobile charging station
Place obtains certain economy return.
In summary, a kind of electric automobile of consideration behavior randomness of the invention participates in the dispatching method of power grid voltage regulating, no
Only can more fit the actual use situation of electric automobile, and can improve the stability of line voltage well, show simultaneously
Reduce the charging spending of automobile user with writing.
Although illustrative embodiment of the invention is described above, in order to the technology of the art
Personnel understand the present invention, it should be apparent that the invention is not restricted to the scope of embodiment, to the common skill of the art
For art personnel, as long as various change is in the spirit and scope of the present invention that appended claim is limited and is determined, these
Change is it will be apparent that all utilize the innovation and creation of present inventive concept in the row of protection.
Claims (2)
1. a kind of electric automobile of consideration behavior randomness participates in power grid voltage regulating dispatching method, it is characterised in that including following step
Suddenly：
(1) the game Competitive Bidding Model of the idle price of electric automobile, is set up
(1.1) the idle price of electric automobile, is calculated：
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From the number of the electric automobile of scheduling；
(1.2) the game Competitive Bidding Model of the idle price of electric automobile, is set up
The deviation of optimal compensation amount needed for reactive-load compensation amount and power network that (1.2.1), calculating charging station are provided for power network, by this
Deviation represents voltage regulation result of the charging station to power network；
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The smaller then voltage regulation result of deviation is better；Optimal reactive-load compensation amount needed for expression power network；
(1.2.2), calculate every automobile user participate in pressure regulation through return；
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Wherein, fEVnThe economy return function that power grid voltage regulating is obtained is participated in by n-th electric automobile；Set s ∈ N { n } represent clothes
Remove n-th electric automobile from all electric automobile set of scheduling；
(1.2.3), choose optimal voltage regulation result and every automobile user desired maximum economy of the charging station to power network
Return constitutes the game Competitive Bidding Model of the idle price of electric automobile；
(2) Profit model of charging station, is set up；
(2.1), charging station obtains that market is active and Reactive Power Price data at power network；
(2.2) charging electric vehicle retail price, is determined according to market active electricity price, equal to γ times of market active electricity price, γ>1；
(2.3) the income sum that the income and participation power grid voltage regulating for, obtaining charging electric vehicle are obtained always is received as charging station
Beneficial Income, will be bought from power network establish by cable branch and pay automobile user participate in pressure regulation expense be used as totle drilling cost Cost, set up
The Profit model of charging station：
Rev=Income-Cost；
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Wherein, st and et represent the whole story of scheduling slot respectively；Scheduling slot is equally divided into multiple time intervals, each time
A length of Δ t during interval；RhRepresent charging electric vehicle retail price in h-th of time interval；γ represents the retail of charging station setting
Valency and the proportionality coefficient of power network market price；WithActive in h-th of time interval and Reactive power marke electricity price is represented respectively；WithRespectively represent n-th electric automobile charged in h-th of time interval consumption active power and to power network inject it is idle
Work(power；
(3) restricted model of line voltage, is set up
According to regulation of the power system to Network Voltage Stability, the restricted model of line voltage is set up：
Vmin≤Vi≤Vmax；
Wherein, VmaxAnd VminThe safe range upper and lower limit of line voltage is represented respectively；ViRepresent i-th in power system topological structure
The voltage of bar bus；
(4) power module of electric automobile access point, is set up
(4.1) on-position of the charging station in power network, i.e. electric automobile access point, are determined；
(4.2), using charging electric vehicle as the burden with power of power network, the reactive power that it injects to power network is as electric network reactive-load
Compensation, calculates the burden with power of all electric automobiles for obeying scheduling of access point and idle sum of exerting oneself, sets up electronic on power network
The power module of automobile access point：
<mrow>
<msubsup>
<mi>P</mi>
<mi>i</mi>
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Wherein, Pi EWithThe burden with power of electric automobile is represented at i-th bus of power network respectively and idle is exerted oneself；
(5), the maximum for the charging station Profit model set up with step (2) turns to object function, with step (3) and step (4)
The line voltage restricted model and the power module of electric automobile access point set up are constraints, set up charging station to electronic
The Optimized Operation mathematical modeling of automobile；
(6) user behavior randomness, is analyzed, estimation electric automobile reaches/left time and the battery electric quantity state of charging station
(SOC)
(6.1) user behavior data, is analyzed, the electric automobile number of charging station is accessed/left to one day each hour of estimation；
(6.1.1) analyzes user behavior data, be fitted by Poisson obtain in one day electric automobile at charging station reach rate/from
Open rate；
(6.1.2), according to it is resulting leave the time of charging station up to/departure rate calculates every two electric automobiles and continuously reached/between
Every, until all vehicles reached/leave charging station：
<mrow>
<mi>&tau;</mi>
<mo>=</mo>
<mo>-</mo>
<mfrac>
<mn>1</mn>
<mi>&lambda;</mi>
</mfrac>
<mi>ln</mi>
<mi>&xi;</mi>
<mo>;</mo>
</mrow>
Wherein, τ represents that every two electric automobiles continuously reach/left the time interval of charging station；λ represents that electric automobile is reached
Rate/departure rate；ξ is obedience (0,1) equally distributed stochastic variable；
(6.1.3) ,/time departure interval reached according to gained, obtain each electric automobile and reach/leave the specific of charging station
Time；
(6.1.4) counts the electric automobile number for each hour reaching/leaving charging station；
(6.2), analyze user behavior data, by just too distribution estimation electric automobile reach when initial cells SOC and leave
Shi Suoxu minimum battery SOC；
(7) the electric automobile relevant parameter, estimated based on step (6) and the basic load obtained at power network, line impedance,
Multiple scheduling slots will be divided into scheduling time, the Optimized Operation set up using sequential quadratic programming method calculation procedure (5)
Mathematical modeling, obtains the charge efficiency of optimum allocation and idle size of exerting oneself in each scheduling slot to each electric automobile,
And as dispatch command of the charging station to electric automobile, and send successively to corresponding automobile user, complete scheduling process.
2. a kind of electric automobile of consideration behavior randomness according to claim 1 participates in power grid voltage regulating dispatching method, its
It is characterised by, the proportionality coefficient m of described excitation electricity pricehComputational methods be：
2.1) target, is turned to automobile user economy return maximum, the idle desired value of exerting oneself of each electric automobile is calculated
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2.2), using charging station to the optimal voltage regulation result of power network as target, calculate each electric automobile under Nash Equilibrium state
Idle desired value of exerting oneself
<mrow>
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2.3), by step 2.1) and 2.2) in idle desired value of exerting oneselfIt is equal, it is determined that the proportionality coefficient m of excitation electricity priceh：
<mrow>
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<mo>.</mo>
</mrow>
3
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| CN107618393A (en) * | 2017-09-29 | 2018-01-23 | 重庆邮电大学 | A kind of charging electric vehicle load control system and method based on lever electricity price |
| CN108964031A (en) * | 2018-07-12 | 2018-12-07 | 电子科技大学 | Electric car charging and the model predictive control method for participating in pressure regulation |
| CN109510250A (en) * | 2018-12-19 | 2019-03-22 | 洁电（北京）储能科技有限公司 | Charging station, charging pile system and control method with power grid ancillary service function |
| CN110733371A (en) * | 2019-10-30 | 2020-01-31 | 深圳供电局有限公司 | electric vehicle charging pile charging analysis method |
| CN110962665A (en) * | 2019-10-24 | 2020-04-07 | 东南大学 | Scattered electric vehicle charging coordination method based on local measurement voltage amplitude |
| CN111347912A (en) * | 2018-12-20 | 2020-06-30 | 勃姆巴迪尔运输有限公司 | System and method for adjusting a charge rate for charging a vehicle battery based on an expected passenger load |
| CN112020450A (en) * | 2018-04-17 | 2020-12-01 | 乌本产权有限公司 | Charging station and method for charging an electric vehicle |
| CN113095557A (en) * | 2021-03-31 | 2021-07-09 | 国网福建省电力有限公司经济技术研究院 | Intelligent charging station planning method based on hybrid user balance theory and charge and discharge management |
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| CN107618393A (en) * | 2017-09-29 | 2018-01-23 | 重庆邮电大学 | A kind of charging electric vehicle load control system and method based on lever electricity price |
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| CN109510250A (en) * | 2018-12-19 | 2019-03-22 | 洁电（北京）储能科技有限公司 | Charging station, charging pile system and control method with power grid ancillary service function |
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| CN110962665A (en) * | 2019-10-24 | 2020-04-07 | 东南大学 | Scattered electric vehicle charging coordination method based on local measurement voltage amplitude |
| CN110962665B (en) * | 2019-10-24 | 2021-04-27 | 东南大学 | Scattered electric vehicle charging coordination method based on local measurement voltage amplitude |
| CN110733371A (en) * | 2019-10-30 | 2020-01-31 | 深圳供电局有限公司 | electric vehicle charging pile charging analysis method |
| CN113095557A (en) * | 2021-03-31 | 2021-07-09 | 国网福建省电力有限公司经济技术研究院 | Intelligent charging station planning method based on hybrid user balance theory and charge and discharge management |
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