CN116215297A - Ordered charging control method considering charging continuity of electric automobile - Google Patents

Ordered charging control method considering charging continuity of electric automobile Download PDF

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Publication number
CN116215297A
CN116215297A CN202111465635.5A CN202111465635A CN116215297A CN 116215297 A CN116215297 A CN 116215297A CN 202111465635 A CN202111465635 A CN 202111465635A CN 116215297 A CN116215297 A CN 116215297A
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charging
load
time
electric automobile
electric
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郭明星
戴峥
莫阮清
傅晨
李峰
顾丹珍
陈菲尔
张超林
刘盼盼
吴建坤
沈晓岚
洪睿洁
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Shanghai University of Electric Power
Economic and Technological Research Institute of State Grid Shanghai Electric Power Co Ltd
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Shanghai University of Electric Power
Economic and Technological Research Institute of State Grid Shanghai Electric Power Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/63—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
    • 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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  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention relates to an orderly charging control method considering charging continuity of an electric automobile, which comprises the following steps: 1) Constructing an electric automobile disordered charging model, and acquiring an electric automobile charging load curve according to the disordered charging model; 2) Constructing an expected charging load model by taking the minimum load fluctuation as an optimization target, and solving to obtain an expected charging load P * The method comprises the steps of carrying out a first treatment on the surface of the 3) According to the desired charging load P * Dividing the optimized total time length into chargeable time periods and non-chargeable time periods, and correcting a charging plan of the electric automobile in the non-chargeable time periods to realize ordered charging control. Compared with the prior art, the method has the advantages of being suitable for the charging scene of electric automobiles with various vehicle types, improving the running benefit of the power grid and the economic benefit of users, along with small calculated amount, short running time and the like.

Description

Ordered charging control method considering charging continuity of electric automobile
Technical Field
The invention relates to the field of electric vehicle charging control, in particular to an ordered charging control method considering electric vehicle charging continuity.
Background
Under the global energy crisis background, electric vehicles are increasingly popular, and large-scale electric vehicles are disordered to charge so as to bring new voltage utilization force to an electric power system. It is particularly important to plan ordered charging of electric vehicles and solve the problem of peak-valley difference expansion caused by charging. The electric automobile has typical dual attributes of load and power supply, has great effect in building a safe, economical and environment-friendly intelligent power system, and is one of important means for solving the problems of traffic, energy and environment.
At present, a plurality of researches related to the participation of electric vehicles in power grid interaction at home and abroad are carried out, the electric vehicles are generally regarded as a flexible energy storage element, and the charging and discharging processes of the electric vehicles are optimally controlled through intelligent charging equipment, so that the aim of assisting in power grid peak shaving or frequency modulation and other auxiliary services is fulfilled, and the researches are mainly carried out from the aspects of technical feasibility, economic evaluation of each participant, scheduling method formulation and the like.
Hu Zechun, song Yonghua and Liu Hui introduce a distributed control principle by using a probability transition matrix-based electric vehicle ordered charging distributed control method and further discuss collapse of a combined layered and distributed hybrid ordered charging architecture and an optimization model, but the scheme needs more basic data, needs to analyze and correct an initial charging plan of each vehicle, and then superimposes and performs convergence analysis according to a convergence criterion, so that the calculated amount is large.
At present, most researches design a control method from the angle of stable operation of a power grid, and when an electric automobile is connected to a charging pile in a specific time period, a control center optimizes a charging plan of each automobile so that the electric automobile can be charged according to the optimized charging plan, and the electric automobile can be completely fitted with an expected load curve to achieve a completely ideal charging state. However, most control methods are used for polymerizing the electric vehicles into a whole from the viewpoint of stable operation of the power grid, so that discontinuous charging conditions can be generated, the individual behaviors of the electric vehicle users and the requirements of charging continuity are practically ignored, and the charging behaviors of the electric vehicles are not consistent with those of actual electric vehicles.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an orderly charging control method considering the charging continuity of electric vehicles, taking the charging continuity of each electric vehicle into consideration, aiming at peak clipping and valley filling, and adopting a cost-benefit evaluation method to influence a system and the electric vehicles.
The aim of the invention can be achieved by the following technical scheme:
an orderly charging control method considering charging continuity of an electric automobile comprises the following steps:
1) Constructing an electric automobile disordered charging model, and acquiring an electric automobile charging load curve according to the disordered charging model;
2) Constructing an expected charging load model by taking the minimum load fluctuation as an optimization target, and solving to obtain an expected charging load P * ；
3) According to the desired charging load P * Dividing the optimized total time length into chargeable time periods and non-chargeable time periods, and correcting a charging plan of the electric automobile in the non-chargeable time periods to realize ordered charging control.
In the step 1), in the unordered charging model of the electric automobile, the charging start SOC of the automobile user is compliant with the expected mu b Variance of
Figure BDA0003391318300000021
Is subjected to the expected mu at the end of charge e Variance->
Figure BDA0003391318300000022
Normal distribution of (c) is:
Figure BDA0003391318300000023
Figure BDA0003391318300000024
Figure BDA0003391318300000025
wherein SOC is b To charge initial power, SOC e To end the charge, t length For the charge duration, C Li The charging capacity of the lithium battery is represented by P, which is the unit charging power.
In the step 1), the expression for acquiring the charging load of the electric automobile based on the unordered charging model of the electric automobile is specifically as follows:
Figure BDA0003391318300000026
wherein P is t For the total charging power at time t, namely the charging load of the electric automobile, P n For the nth vehicle from the charging start time t b To (t) b +t length ) Charging power at time.
In the step 2), the expected charging load model with the minimum load fluctuation as the optimization target includes:
Figure BDA0003391318300000027
the constraint conditions include:
total power constraint condition of electric vehicle:
Figure BDA0003391318300000031
total energy constraint of electric vehicle:
Figure BDA0003391318300000032
wherein P is t Charging load for electric automobile at t moment, L t L is a normal load av As an average value of the conventional load,
Figure BDA0003391318300000033
rated for n-th automobile, eta c For charging efficiency E n For the nth car energy, Γ is a time series dividing the optimized total duration according to a set time interval, v is the total number of controlled electric cars, and Δt is the set time interval.
The step 3) specifically comprises the following steps:
31 According to the desired charging load P) * Obtaining a charging plan and a chargeable time sequence T of a current power grid enable ＝{T 1 ,T 2 ,T 3 …T m }；
32 When the electric vehicle is in the uncharged period, correcting the charging schedule of the electric vehicle in the uncharged period, and starting the original charging of the electric vehicle at the time t b To the nearest chargeable period T 1 When the transferred chargeable period charging load exceeds the corresponding expected charging load, then the next chargeable period T is transferred 2 Charging is started.
In said step 31), according to the desired charge load P * The chargeable time series is obtained specifically as follows:
Figure BDA0003391318300000034
T enable ＝{T 1 ,T 2 ,T 3 …T m }
wherein S is (t) For the charging schedule at time t, S (t) When 0 is not chargeable at time t, S (t) When 1, the charging is carried out at the time t, P * (t) The desired charge load at time t is indicated, and a is the set power threshold.
The value of the power threshold value a is 1kW.
In the step 32), the judging basis for judging whether the electric automobile is in the non-chargeable period is specifically as follows:
Figure BDA0003391318300000035
Figure BDA0003391318300000036
wherein C is n Charging plan for nth electric automobile, C n,t C, an initial charging plan of the nth electric automobile at t time n,t When the value is 0, the charging is not performed at the time t, C n,t When 1, the planned charging is indicated at the time t, t n And charging the nth electric automobile.
The method further comprises the steps of:
4) And evaluating the control effect.
The step 4) is specifically as follows:
the load rate is used as an index of the running benefit of the power grid to evaluate the control effect, and from the perspective of a user, the economic benefit is used as an index of the user to evaluate the control effect.
Compared with the prior art, the invention has the following advantages:
1. according to the method, the charging behaviors of the users of the electric automobiles of different vehicle types are considered, and the ordered charging control method is formulated according to the charging behaviors, so that the method has universality and can be suitable for the charging scenes of the electric automobiles of various vehicle types.
2. The invention improves the running benefit of the power grid and the economic benefit of the electric automobile user.
3. The method has the advantages of simpler model, smaller calculated amount, shorter running time and time cost saving in practical application.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a daily charge load curve of the electric vehicle.
Fig. 3 is a total daily load curve.
Fig. 4 shows the load factor of various electric vehicles.
Fig. 5 is an electric vehicle charging cost.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples.
Examples
The invention provides an ordered charging control method considering charging continuity of an electric automobile, which comprises the steps of firstly establishing an unordered charging model of the electric automobile, establishing an objective function from the angle of safe operation of a power grid to obtain expected charging load of the electric automobile, designing a control method of ordered charging of the electric automobile on the premise of considering charging continuity of users of the electric automobile, optimizing charging load models of electric automobiles of different automobile types based on the control method, analyzing operation benefits of the power grid and economic benefits of the users of the electric automobile before and after optimization, and finally further showing that the control method has obvious effects of improving the operation benefits of the power grid and reducing the electricity cost of the users of the electric automobile through case analysis.
The invention is specifically described as follows
1. Electric automobile charging load model and regulation and control method
1.1 electric automobile charging load model (electric automobile unordered charging model)
The charge load curve of an electric vehicle is usually obtained by superposition of the charge load of each vehicle, and the charge start SOC of a vehicle user is compliant with the expected mu b Variance of
Figure BDA0003391318300000051
Is subjected to the expected mu at the end of charge e Variance->
Figure BDA0003391318300000052
Normal distribution of (c), namely:
Figure BDA0003391318300000053
Figure BDA0003391318300000054
Figure BDA0003391318300000055
wherein: SOC (State of Charge) b The initial charge quantity is used for charging; SOC (State of Charge) e Ending the electric quantity for charging; t is t length The charging time is the charging time; c (C) Li Charge capacity for lithium battery; p is the unit charging power.
Assuming that there are n vehicles, if the charging start time of the nth vehicle is t b Then the nth vehicle starts from the charging start time t b To (t) b +t length ) The charging power at the moment is P n Assume that the total charging power at time t is P t ，P n The total charging power at the time t is the charging power at the time t of the nth vehicle, namely the charging load is as follows:
Figure BDA0003391318300000056
1.2 Regulation and control method
1.2.1 desired charging load model
The unordered charging of the electric automobile aggravates load fluctuation, expands load peak-valley difference and threatens the stable and safe operation of a power grid, when an ordered charging optimization model is established from the view of the safe operation of the power grid, the minimum load fluctuation is set as an optimization target, when a constraint condition is established, whether the total value of charging loads before and after optimization is consistent is considered, and then the required total energy of each automobile is unchanged, the objective function and the constraint condition are as follows:
objective function:
F 1 ＝min∑ t∈Γ (P t +L t -L av ) 2 (5)
total power constraint condition of electric vehicle:
Figure BDA0003391318300000057
total energy constraint of electric vehicle:
η c ∑ t∈T P t ΔT＝∑ n∈v E n (7)
obtaining the expected charging load P through optimizing and solving * 。
Wherein P is t The charging load at the time t; l (L) t Is a conventional load; l (L) av Is the average value of the conventional load;
Figure BDA0003391318300000058
rated power for the nth car; η (eta) c Is the charging efficiency; e (E) n For the nth car energy Γ is a time sequence divided according to a set time interval, v is the total number of controlled electric cars, Δt is the time interval.
1.2.2 control methods
The control center calculates the expected charging load P according to the calculated * The time of day can be divided into a chargeable period and a non-chargeable period, the user of the automobile in the chargeable period charges according to the original plan, the charging plan of the automobile in the non-chargeable period is initialized, the charging plan is transferred to the chargeable period, and the charging plan is compared with the expected load after each superposition, if the charging load of the charging period reaches the expected value, the charging plan of the next electric automobile is continued to the next chargeable period until the charging plans of all the electric automobiles in the non-chargeable period are optimized.
First by the desired charge load P * Searching for a period of time during which the current power grid can be charged, and constraint conditions are as follows:
Figure BDA0003391318300000061
T＝{T 1 ,T 2 ,T 3 …T m } (9)
wherein S is (t) For the charging schedule at time t, S (t) When 0 is not chargeable at time t, S (t) When the value is 1, the charging is carried out at the time t; p (P) * (t) Indicating a desired charge load at time t; t is a chargeable time sequence { T ] 1 ,T 2 ,T 3 …T m }；
Judging whether the electric automobile is in a non-chargeable period or not according to the following judgment basis;
Figure BDA0003391318300000062
Figure BDA0003391318300000063
C n a charging plan for an nth electric vehicle; c (C) n,t C, an initial charging plan of the nth electric automobile at t time n,t When 0, it indicates that the battery is not charged at time t，C n,t When the charging is 1, the planned charging at the time t is indicated; t is t n The time Γ for charging the nth electric car is a time series {1,2,3 … Γ } divided according to a set time interval.
Correcting the automobile charging schedule in the uncharged period, and starting the original charging at the time t b Transfer to chargeable period and from T 1 The charging is started in the period, and the charging is carried out according to the original charging time length, so that the charging time of the electric vehicle cannot be arbitrarily compressed or the charging of the electric vehicle cannot be interrupted due to the fact that the stable operation of the power grid is not guaranteed in a certain period of time, and when T 1 When the charging load at the moment reaches the expected value, then T is taken as the following 2 The period starts charging, and so on, and the solution flow chart is shown in fig. 1.
2. Cost-benefit evaluation model for different vehicle types
The influence of the electric automobile access power grid on the power grid is mainly reflected in the aspect of load fluctuation, so that the load rate is used as a power grid operation benefit index, namely:
T 2 ＝p′ av /max(L(t)) (12)
wherein: f (F) 2 Is the load factor; l (t) is the total load taking into account the charging load; p'. av Is the average value of L (t).
From the perspective of a user, the charging behavior of the battery can change along with the change of charging cost, so that economic benefits are used as evaluation indexes of the user, and the calculation formula is as follows:
Figure BDA0003391318300000071
p＝p s +p r (14)
wherein: c is the electricity cost of the electric automobile user; t (T) n Charging time for the nth vehicle; p is the cost per unit time; p (P) n Charging power for the nth vehicle; p is p s Is a service fee; p is p r Is the electricity charge.
3. Case analysis
3.1 Car-Net interaction basic model
The daily running condition of a power grid in certain city and summer is selected as a case for analysis, a basic load curve is shown as a yellow line in fig. 2, in an example simulation, the total optimization period is 24 hours, the set time interval is 15 minutes, a day is divided into 96 time periods, and 10000 private cars (PHEV), private cars (BEV), logistics cars, buses, public service cars (PHEV) and public service cars (BEV) are assumed to participate in the power grid peak regulation plan, and various electric car parameter indexes are shown in table 1.
Table 1 various electric automobile parameter indexes
Figure BDA0003391318300000072
Based on the table 1 and the probability distribution of the starting moment of the electric automobile, the electric automobile unordered charging model is used for modeling, so that daily charging load curves of electric automobiles of different automobile types can be obtained, and the total load curve of the electric automobile can be obtained after accumulation.
3.2 implementation effects of ordered charging methods
And optimizing by using the expected charging load model to obtain an expected load curve, as shown in fig. 3. Assuming that the electric automobile is connected with a charging pile when the electric automobile is in a low-valley section of the power grid load, the control center can obtain information such as electric quantity of the electric automobile, correct the charging schedule of the original electric automobile by using a regulation and control method, charge the electric automobile according to the optimized charging schedule, and various charging load curves of the electric automobile before and after correction and the overall charging load curve of the electric automobile are shown in fig. 3.
As can be seen from fig. 2, the charging load characteristics of electric vehicles of different vehicle types are different, and the peak sections of electricity consumption are also different, the peak of electricity consumption of a passenger car is concentrated at ten am and eight pm to ten pm, the peak of electricity consumption of a bus is concentrated at early morning and noon, the peak of electricity consumption of a bus is concentrated at evening, the peak of electricity consumption of a private car is concentrated at ten am and night, and the peak of electricity consumption of a power grid is concentrated at ten am to about eight pm, so that the original charging load is optimized according to formulas (5) - (7), and the expected load curve shown in fig. 3 is obtained.
As can be seen from fig. 3, the expected load curve is the most ideal state for minimizing the fluctuation of the power grid, however, the actual situation is affected by more factors and cannot be completely fitted with the expected load curve, while the invention considers the user behavior of the electric vehicle and the power grid benefit to develop a control method according to which the original charging load can be corrected, the corrected curve is shown as the corrected load curve in fig. 3, and by means of the control method, after the charging load of the electric vehicle from eight in the morning to ten in the evening is transferred to ten in the evening, the charging load of the electric vehicle and the expected load are basically fitted, thereby achieving the peak clipping and valley filling effects.
3.3 electric vehicle cost-benefit evaluation
According to the peak-valley electricity price of Shanghai city, based on a peak-valley clipping and filling model (a vehicle-network interaction basic model), obtaining an optimized charging plan of each vehicle, and calculating the load rates of the power grids before and after ordered charging of different vehicle types according to a formula (12), wherein a load rate graph is shown in fig. 4. Parameters such as power price, service charge and the like of the Shanghai utility grid are shown in table 2, wherein the power grid income is derived from the service charge and the power charge of the electric automobile charging, and the power grid cost comprises the operation maintenance charge and the electricity purchasing cost of the charging pile.
Based on the parameters of table 2, the electricity cost and the power grid running load rate of the electric automobile users before and after orderly charging based on the control method are calculated, and the results are shown in fig. 4 and 5.
TABLE 2 principal economic parameters
Figure BDA0003391318300000081
Fig. 4 shows the influence of the electric vehicles of different vehicle types on the power grid load factor by participating in the power grid peak shaving before and after ordered charging from the angle of the power grid. Through graph analysis, the ordered charging of all vehicle types is closer to 1 in power grid load rate compared with disordered charging, namely, the power grid running benefit is better, and the load fluctuation is more stable. Compared with the load rates of different vehicle types after ordered charging, the load rate of a private vehicle (PHEV) is increased by 0.07%, the load rate of a private vehicle (BEV) is increased by 0.15%, the load rate of a logistics vehicle is increased by 0.36%, the load rate of a bus is increased by 1.45%, the load rate of a bus is increased by 1.26%, the load rate of a public service vehicle (PHEV) is increased by 0.06%, and the load rate of a public service vehicle (BEV) is increased by 0.13%. The running benefit of the power grid is increased by 0.50% on average. Therefore, the power grid load rate of the buses and buses before and after orderly charging changes the most, namely, the buses and buses have the greatest contribution to the stability of the power grid compared with other types of electric vehicles under the same condition. From quick charge and slow charge angle analysis, logistics vehicles, buses and buses all adopt a quick charge charging mode, and private vehicles and public service vehicles adopt a slow charge charging mode. The graph shows that the electric automobile has better stability to the power grid by adopting a quick charging mode.
Fig. 5 calculates the user costs for ordered and unordered charging from a user perspective. From the figure, the cost of various electric automobile users is obviously reduced after ordered charging. Wherein, private car (PHEV) charging cost is reduced by 10.52%, private car (BEV) charging cost is reduced by 9.17%, logistics car charging cost is reduced by 13.05%, bus charging cost is reduced by 13.88%, bus charging cost is reduced by 7.68%, public service car (PHEV) charging cost is reduced by 3.27%, and public service car (BEV) charging cost is reduced by 2.62%. Therefore, the average electricity cost of electric vehicles of different vehicle types is reduced by 8.60% after the electric vehicles participate in orderly charging, and the cost of logistics vehicles and buses is reduced to the greatest extent.
In conclusion, the control method adopted by the invention has obvious peak clipping and valley filling effects on the power system, and improves the peak clipping capacity of the system; by comparing the electricity consumption cost of the electric vehicles of each vehicle type before and after ordered charging, the control method adopted by the invention guides the electric vehicle user to charge in a more proper period, and the cost of the vehicle owner is reduced; the charging experience of the vehicle owner is improved by ensuring the charging continuity of the electric vehicle.

Claims (10)

1. An orderly charging control method considering charging continuity of an electric automobile is characterized by comprising the following steps:
1) Constructing an electric automobile disordered charging model, and acquiring an electric automobile charging load curve according to the disordered charging model;
2) With minimum load fluctuation as an optimization targetBuilding an expected charging load model, and solving to obtain an expected charging load P * ；
3) According to the desired charging load P * Dividing the optimized total time length into chargeable time periods and non-chargeable time periods, and correcting a charging plan of the electric automobile in the non-chargeable time periods to realize ordered charging control.
2. The method according to claim 1, wherein in the step 1), in the disordered charge model of the electric vehicle, the charge start SOC of the vehicle user is compliant with the expected μ b Variance of
Figure FDA0003391318290000011
Is subjected to the expected mu at the end of charge e Variance->
Figure FDA0003391318290000012
Normal distribution of (c) is:
Figure FDA0003391318290000013
Figure FDA0003391318290000014
Figure FDA0003391318290000015
wherein SOC is b To charge initial power, SOC e To end the charge, t length For the charge duration, C Li The charging capacity of the lithium battery is represented by P, which is the unit charging power.
3. The method for orderly charging control according to claim 2, wherein in the step 1), the expression for obtaining the charging load of the electric vehicle based on the disordered charging model of the electric vehicle is specifically as follows:
Figure FDA0003391318290000016
wherein P is t For the total charging power at time t, namely the charging load of the electric automobile, P n For the nth vehicle from the charging start time t b To (t) b +t length ) Charging power at time.
4. The method for orderly charging control according to claim 3, wherein in the step 2), the expected charging load model with the minimum load fluctuation as the optimization target comprises:
Figure FDA0003391318290000021
the constraint conditions include:
total power constraint condition of electric vehicle:
Figure FDA0003391318290000022
total energy constraint of electric vehicle:
Figure FDA0003391318290000023
wherein P is t Charging load for electric automobile at t moment, L t L is a normal load av As an average value of the conventional load,
Figure FDA0003391318290000024
rated for n-th automobile, eta c For charging efficiency E n For the nth car energy, Γ is a time series dividing the optimized total duration according to a set time interval, v is the total number of controlled electric cars, and Δt is the set time interval. />
5. The method for orderly charging control according to claim 4, wherein said step 3) comprises the steps of:
31 According to the desired charging load P) * Obtaining a charging plan and a chargeable time sequence T of a current power grid enable ＝{T 1 ，T 2 ，T 3 ...T m }；
32 When the electric vehicle is in the uncharged period, correcting the charging schedule of the electric vehicle in the uncharged period, and starting the original charging of the electric vehicle at the time t b To the nearest chargeable period T 1 When the transferred chargeable period charging load exceeds the corresponding expected charging load, then the next chargeable period T is transferred 2 Charging is started.
6. The method according to claim 5, wherein in the step 31), the charging control unit is configured to control the charging load according to the desired charging load P * The chargeable time series is obtained specifically as follows:
Figure FDA0003391318290000025
T enable ＝{T 1 ，T 2 ，T 3 ...T m }
wherein S is (t) For the charging schedule at time t, S (t) When 0 is not chargeable at time t, S (t) When 1, the charging is carried out at the time t, P * (t) The desired charge load at time t is indicated, and d is the set power threshold.
7. The method for orderly charging control according to claim 6, wherein the power threshold d is 1kW.
8. The method according to claim 6, wherein in the step 32), the judgment criterion for judging whether the electric vehicle is in the non-chargeable period is specifically as follows:
Figure FDA0003391318290000031
C n ＝0；
Figure FDA0003391318290000032
t b ＜t n ＜t b +t length
wherein C is n Charging plan for nth electric automobile, C n，t C, an initial charging plan of the nth electric automobile at t time n，t When the value is 0, the charging is not performed at the time t, C n，t When 1, the planned charging is indicated at the time t, t n And charging the nth electric automobile.
9. The method of orderly charge control taking into account electric vehicle charge continuity according to claim 1, further comprising the steps of:
4) And evaluating the control effect.
10. The method for orderly charging control according to claim 9, wherein the step 4) specifically comprises:
the load rate is used as an index of the running benefit of the power grid to evaluate the control effect, and from the perspective of a user, the economic benefit is used as an index of the user to evaluate the control effect.
CN202111465635.5A 2021-12-03 2021-12-03 Ordered charging control method considering charging continuity of electric automobile Pending CN116215297A (en)

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