CN110406422B - Electric bus battery participation V2G control method considering multi-party benefits - Google Patents

Electric bus battery participation V2G control method considering multi-party benefits Download PDF

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CN110406422B
CN110406422B CN201910708078.1A CN201910708078A CN110406422B CN 110406422 B CN110406422 B CN 110406422B CN 201910708078 A CN201910708078 A CN 201910708078A CN 110406422 B CN110406422 B CN 110406422B
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electric bus
bus
electric
battery
time
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CN110406422A (en
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钱科军
秦晓阳
刘乙
秦萌
陈丽娟
童充
张政
郑众
马千里
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Southeast University
Suzhou Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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Suzhou Power Supply Co of State Grid Jiangsu 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
    • B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means

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Abstract

The application discloses electric bus battery participation V2G control method taking multi-party benefits into consideration, which comprises the following steps: acquiring day-ahead electricity price, load data and a bus running schedule; establishing a progressive bus management mode; calculating the available V2G charge/discharge capacity of the electric bus battery cluster at any moment; establishing an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model; establishing an electric bus battery cluster multi-objective optimization model; and solving to obtain a charging/discharging plan of the electric bus battery cluster under the time scale of the day ahead. According to the invention, the available V2G charge/discharge capacity of the electric bus battery cluster at any time is calculated on the basis of a 'progressive' electric bus management mode, and is used as the constraint condition of an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model, and meanwhile, the optimal control strategy of the electric bus battery cluster participating in V2G is obtained by adopting a multi-objective optimization method.

Description

Electric bus battery participation V2G control method considering multi-party benefits
Technical Field
The invention belongs to the technical field of Vehicle-network interaction (V2G), and relates to a V2G control method for battery participation of an electric bus considering multi-party benefits, in particular to a V2G control method for battery cluster participation of an electric bus considering benefits of both an electric bus company and a power grid.
Background
As the infiltration rate of electric vehicles into the power grid increases, the charging/discharging behavior of electric vehicles presents new challenges to the operation of the power grid. Due to the random charging/discharging behavior and the large charging load of a large number of electric vehicles, the safe operation of the power grid is significantly affected, and thus various potential problems, such as reduced power quality, voltage fluctuations and overload, are caused. In order to solve the negative influence of the disordered charging/discharging behaviors of the electric automobile on a power grid, an ordered charging/discharging strategy of the electric automobile has positive significance.
At present, the electric automobile is most widely applied to two fields of electric taxies and electric buses. However, there have been studies on the electric bus cluster participating in the V2G dispatching strategy, and most studies have been from the viewpoints of battery endurance, charging mode, and new energy dispatching at a charging station, and the like, and although some studies have considered the stakeholders in V2G, some studies have considered only single stakeholders, and have not considered multi-party benefits.
Disclosure of Invention
In order to solve the defects in the prior art, the application provides the control method of the participation V2G of the battery of the electric bus considering multi-party benefits, and the problem of inconsistent benefits between an electric bus company and a power grid is effectively solved.
In order to achieve the above purpose, the invention adopts the following technical scheme:
an electric bus battery participation V2G control method considering multi-party benefits comprises the following steps:
step 1: acquiring day-ahead electricity price, load data and a bus running schedule;
step 2: establishing a progressive bus management mode based on a bus running schedule;
and step 3: calculating the available V2G charge/discharge capacity of the electric bus battery cluster at any moment based on the progressive bus management mode;
and 4, step 4: establishing an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model based on the day-ahead electricity price, load data and the available V2G charging/discharging capacity of the electric bus battery cluster at any moment;
and 5: establishing an electric bus battery cluster multi-objective optimization model based on an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model;
step 6: and solving the multi-objective optimization model of the electric bus battery cluster to obtain a charging/discharging plan of the electric bus battery cluster under the time scale of the day ahead.
The invention further comprises the following preferred embodiments:
step 2, establishing a progressive bus management mode based on the bus running schedule, specifically comprising the following steps:
determining 6 state time intervals delta T in the progressive bus management mode according to the departure time, the arrival charging time and the vehicle outage time of the electric bus in the electric bus running schedulei(i ∈ {1,2,. 6}), which are: the electric bus partially departs from the bus, partially participates in V2G, partially participates in bus operation, partially participates in V2G, partially enters the station for charging, partially departs from the bus, partially participates in V2G, partially participates in bus operation, partially participates in V2G, partially stops the bus, partially participates in V2G, and completely participates in V2G;
preferably, the electric bus battery cluster at any time in step 3 may use V2G charge/discharge capacity, and the calculation formula is as follows:
Figure GDA0003349646010000021
Figure GDA0003349646010000022
Figure GDA0003349646010000023
Figure GDA0003349646010000024
Figure GDA0003349646010000025
Figure GDA0003349646010000031
Figure GDA0003349646010000032
in the formula, CD(k Δ t) is the available V2G discharge capacity, CC(k Δ t) is the available V2G charge capacity; cD(k0Δ T) is Δ T1Available V2G discharge capacity at the start time; n is a radical ofkIs DeltaT1、ΔT3、ΔT5The corresponding bus shift of departure, arrival charging and stop at any time in the three state time periods; lambda [ alpha ]kThe number of buses for departure, arrival charging and stop of each class; delta CT(kiΔ t) (i belongs to {1,2,. and 6}) is the total capacity change amount of the electric bus battery cluster participating in V2G at any time; SOCresIs DeltaT3When each electric bus enters the station and is charged within the state time interval and the time difference is delta T5The average residual SOC value of the vehicle-mounted single batteries when each electric bus returns to the charging station after stopping in the state time period; Δ t is the minimum scheduling time interval; n is a radical ofv2g(k Δ T) represents Δ T1-ΔT6The total number of the electric buses participating in V2G at any k delta t moment in different state periods; cbatThe rated capacity of the single battery is stated in kWh; SOCminAnd SOCmaxRespectively, the lower limit and the upper limit of the state of charge SOC of the unit cell.
Preferably, the model for minimizing the operation cost of the electric bus company in step 4 is as follows:
Figure GDA0003349646010000033
wherein, CCOMThe operating cost of the electric bus company participating in the standby service market in the day-ahead;
Figure GDA0003349646010000034
cost of electric energy interaction for the public transport company-the grid;
Figure GDA0003349646010000035
providing reserve income of ascending/descending reserve service for a power grid for a public transport company;
Figure GDA0003349646010000036
the cost of battery loss caused by charging and discharging of each electric bus.
Preferably, the cost of the bus company-grid for the electric energy interaction
Figure GDA0003349646010000037
Standby revenue for public transport companies to provide up/down standby service to the grid
Figure GDA0003349646010000038
And the cost of battery loss caused by charging and discharging of each electric bus
Figure GDA0003349646010000039
The calculation formula is as follows:
Figure GDA00033496460100000310
Figure GDA00033496460100000311
Figure GDA0003349646010000041
in formula (9), rc(k Δ t) and rd(k delta t) respectively represents the charging/discharging real-time electricity price of the bus company at any time from the power grid, and the unit is $/kWh;
Figure GDA0003349646010000042
represents the charging power of the electric bus n at any moment,
Figure GDA0003349646010000043
the discharge power of the electric bus n at any moment is represented, and the unit is kW;
in the formula (10), gup(k.DELTA.t) and gdw(k Δ t) represents the rising and falling reserve capacity prices received by the public transport company from the power grid at any time, respectively, in units of $/kWh;
Figure GDA0003349646010000044
and
Figure GDA0003349646010000045
respectively representing the rising and falling standby capacities which can be provided by the electric buses at any time, wherein the unit is kW;
in formula (11), CdThe unit battery loss cost of the electric bus is expressed in $/kWh, and the calculation formula is as follows:
Figure GDA0003349646010000046
in the formula, CcThe investment cost of the battery is $; l iscThe number of times of recycling of the battery is set; DOD denotes depth of discharge.
Preferably, in step 4, the model for minimizing the peak-to-valley difference of the load of the power grid is as follows:
min RLoad＝max[PL(kΔt)+PE(kΔt)]-min[PL(kΔt)+PE(kΔt)] (13)
in the formula, PL(k delta t) is a conventional load at any moment in a local power grid control area; pEAnd (k delta t) is the total charging/discharging power of the electric bus battery cluster at any moment.
Preferably, in step 5, the electric bus battery cluster multi-objective optimization model is established based on the electric bus company operation cost minimization model and the power grid load peak-valley difference minimization model, and specifically includes:
respectively aiming at the operation cost C by adopting a min-max standardized methodCOMAnd the peak-valley difference R of the load of the power gridLoadAnd carrying out normalization to obtain dimensionless variables C and R, thereby obtaining the multi-objective optimization model of the weighting method.
Preferably, the multi-objective optimization model is:
min(w1C+w2R) (14)
in the formula, w1And w2Respectively the weight value w of two targets of the operation cost of a public transport company and the load peak-valley difference of a power grid1+w2＝1。
Preferably, the constraint conditions of the multi-objective optimization model are as follows:
Figure GDA0003349646010000051
Figure GDA0003349646010000052
Figure GDA0003349646010000053
Figure GDA0003349646010000054
Figure GDA0003349646010000055
Figure GDA0003349646010000056
Figure GDA0003349646010000057
Figure GDA0003349646010000058
Figure GDA0003349646010000059
Figure GDA00033496460100000510
wherein, the formulas (15) and (16) are the charging/discharging power constraints of a single electric bus,
Figure GDA00033496460100000511
the maximum charge/discharge power of the electric bus n, namely rated power, is represented by kW;
equations (17), (18), (19) are the charge/discharge power constraints for a single electric bus taking into account the reserve capacity;
equations (20), (21) and (22) are the single electric bus state of charge SOC constraints, wherein,
Figure GDA00033496460100000512
the battery SOC value represents the moment when the electric bus n is connected to the power grid;
Figure GDA00033496460100000513
andSOCrespectively is the lower limit and the upper limit of the SOC of the battery of the electric bus; k'Is [1, 24/delta t ]]Any integer in between;
Figure GDA00033496460100000514
and
Figure GDA00033496460100000515
respectively representing the moment when the electric bus n is connected to and separated from the power grid;
equation (23) (24) is the available charge/discharge capacity constraint for the electric bus battery cluster, where CC(k.DELTA.t) and CD(k Δ t) represents the available V2G charging capacity and the available V2G discharging capacity of the electric bus battery cluster at any moment respectively; pE(k Δ t) represents the total charge/discharge power of the electric bus battery cluster at any time, Pdw(k.DELTA.t) and PupAnd (k delta t) respectively represents the total descending reserve capacity and the ascending reserve capacity of the electric bus battery cluster at any time.
Preferably, the total charging/discharging power P of the electric bus battery cluster at any timeE(k delta t), total rising reserve capacity P of electric bus battery cluster at any timedw(k Δ t) and reduced spare capacity Pup(k Δ t), which is calculated as follows:
Figure GDA0003349646010000061
Figure GDA0003349646010000062
Figure GDA0003349646010000063
the beneficial effect that this application reached:
1. the invention establishes a progressive electric bus management mode, calculates the charging/discharging capacity of V2G available for the electric bus battery cluster at any time on the basis, and takes the charging/discharging capacity as the constraint conditions of an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model to embody the driving characteristics of the electric bus and the cluster orderliness.
2. The invention takes multi-party benefits into consideration, namely, two most main benefit correlators of an electric bus company and a power grid are comprehensively considered, and an optimal control strategy of the electric bus battery cluster participating in V2G is obtained by adopting a multi-objective optimization method from two objectives of operation cost and load peak-valley difference.
Drawings
FIG. 1 is a flow chart of a method for controlling the participation of a battery of an electric bus in V2G in consideration of the benefits of multiple parties according to the present invention;
FIG. 2 is a schematic diagram illustrating a progressive management mode of a battery cluster of an electric bus according to an embodiment of the present invention;
FIG. 3 is local load data in an embodiment of the present invention;
fig. 4 is a graph of the local real-time electricity prices and the up/down reserve capacity prices in an embodiment of the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 1, the method for controlling the battery participation V2G of the electric bus in consideration of multi-party interests includes the following steps:
step 1: acquiring day-ahead electricity price, load data and a bus running schedule;
step 2: based on the bus running schedule, a progressive bus management mode is established, and the method specifically comprises the following steps:
as shown in FIG. 2, 6 status periods DeltaT in the progressive bus management mode are determined according to the departure time, the arrival charging time and the vehicle outage time of the electric bus in the electric bus operation schedulei(i ∈ {1,2,. 6}), which are: the electric bus partially departs from the bus, partially participates in V2G, partially participates in bus operation, partially participates in V2G, partially enters into the station for charging, partially departs from the bus, partially participates in V2G, and partially participates in bus operation and divisionThe part is participated in V2G, the part is stopped, the part is participated in V2G, and the whole part is participated in V2G;
and step 3: calculating the available V2G charge/discharge capacity of the electric bus battery cluster at any moment based on the progressive bus management mode;
in the embodiment, the charging/discharging capacity of the electric bus battery cluster at any time can be V2G, and the calculation formula is as follows:
Figure GDA0003349646010000071
Figure GDA0003349646010000072
Figure GDA0003349646010000073
Figure GDA0003349646010000074
Figure GDA0003349646010000081
Figure GDA0003349646010000082
Figure GDA0003349646010000083
in the formula, CD(k Δ t) is the available V2G discharge capacity, CC(k Δ t) is the available V2G charge capacity; cD(k0Δ T) is Δ T1Available V2G discharge capacity at the start time; n is a radical ofkIs DeltaT1、ΔT3、ΔT5Departure and entrance corresponding to any time in three state time periodsBus shifts of station charging and shutdown; lambda [ alpha ]kThe number of buses for departure, arrival charging and stop of each class; delta CT(kiΔ t) (i belongs to {1,2,. and 6}) is the total capacity change amount of the electric bus battery cluster participating in V2G at any time; SOCresIs DeltaT3When each electric bus enters the station and is charged within the state time interval and the time difference is delta T5The average residual SOC value of the vehicle-mounted single batteries when each electric bus returns to the charging station after stopping in the state time period; Δ t is the minimum scheduling time interval; n is a radical ofv2g(k Δ T) represents Δ T1-ΔT6The total number of the electric buses participating in V2G at any k delta t moment in different state periods; cbatThe rated capacity of the single battery is stated in kWh; SOCminAnd SOCmaxRespectively, the lower limit and the upper limit of the state of charge SOC of the unit cell.
And 4, step 4: establishing an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model based on the day-ahead electricity price, load data and the available V2G charging/discharging capacity of the electric bus battery cluster at any moment;
in an embodiment, the cost of operation C of the electric bus company participating in the future standby service marketCOMThe medicine consists of three parts: cost of power interaction (including buying and selling power) for public transport company-power grid
Figure GDA0003349646010000084
Figure GDA0003349646010000084
② the spare income of the public transport company for providing the ascending/descending spare service for the power grid
Figure GDA0003349646010000085
Cost of battery loss caused by charging and discharging of each electric bus
Figure GDA0003349646010000086
The operation cost minimization model of the electric bus company is as follows:
Figure GDA0003349646010000087
Figure GDA0003349646010000088
Figure GDA0003349646010000091
Figure GDA0003349646010000092
in formula (9), rc(k Δ t) and rd(k delta t) respectively represents the charging/discharging real-time electricity price of the bus company at any time from the power grid, and the unit is $/kWh;
Figure GDA0003349646010000093
represents the charging power of the electric bus n at any moment,
Figure GDA0003349646010000094
the discharge power of the electric bus n at any moment is represented, and the unit is kW;
in the embodiment, in order to enhance the electric energy interaction between the battery cluster of the electric bus and the power grid under the management and control of the bus company, the electric bus obtains the reward, namely r when discharging according to the feedback incentive policyd(kΔt)＝rc(k Δ t) + s, where s is a positive real number representing the premium electricity price for the electric bus participating in V2G in $/kWh to encourage the electric bus company to control the electric bus cluster to discharge.
In the formula (10), gup(k.DELTA.t) and gdw(k Δ t) represents the rising and falling reserve capacity prices received by the public transport company from the power grid at any time, respectively, in units of $/kWh;
Figure GDA0003349646010000095
and
Figure GDA0003349646010000096
respectively representing the rising and falling standby capacities which can be provided by the electric buses at any time, wherein the unit is kW;
in formula (11), CdThe unit battery loss cost of the electric bus is expressed in $/kWh, and the calculation formula is as follows:
Figure GDA0003349646010000097
in the formula, CcThe investment cost of the battery is $; l iscThe number of times of recycling of the battery is set; DOD denotes depth of discharge.
The power grid load peak-valley difference minimization model is as follows:
min RLoad＝max[PL(kΔt)+PE(kΔt)]-min[PL(kΔt)+PE(kΔt)] (13)
in the formula, PL(k delta t) is a conventional load at any moment in a local power grid control area; pEAnd (k delta t) is the total charging/discharging power of the electric bus battery cluster at any moment.
And 5: based on the electric bus company operation cost minimization model and the power grid load peak-valley difference minimization model, the electric bus battery cluster multi-objective optimization model is established, and the method specifically comprises the following steps:
respectively aiming at the operation cost C by adopting a min-max standardized methodCOMAnd the peak-valley difference R of the load of the power gridLoadAnd carrying out normalization to obtain dimensionless variables C and R, thereby obtaining the multi-objective optimization model of the weighting method.
In an embodiment, the multi-objective optimization model is:
min(w1C+w2R) (14)
in the formula, w1And w2Respectively the weight value w of two targets of the operation cost of a public transport company and the load peak-valley difference of a power grid1+w2＝1。
In an embodiment, the multi-objective optimization model needs to satisfy constraint conditional equations (15) - (27).
Figure GDA0003349646010000101
Figure GDA0003349646010000102
Figure GDA0003349646010000103
Figure GDA0003349646010000104
Figure GDA0003349646010000105
Figure GDA0003349646010000106
Figure GDA0003349646010000107
Figure GDA0003349646010000108
Figure GDA0003349646010000109
Figure GDA00033496460100001010
Wherein, the formulas (15) and (16) are the charging/discharging power constraints of a single electric bus,
Figure GDA00033496460100001011
the maximum charge/discharge power of the electric bus n, namely rated power, is represented by kW;
equations (17), (18), (19) are the charge/discharge power constraints for a single electric bus taking into account the reserve capacity;
equations (20), (21) and (22) are the single electric bus state of charge SOC constraints, wherein,
Figure GDA0003349646010000111
the battery SOC value represents the moment when the electric bus n is connected to the power grid;
Figure GDA0003349646010000112
andSOCrespectively is the lower limit and the upper limit of the SOC of the battery of the electric bus; k' is [1,24/Δ t ]]Any integer in between;
Figure GDA0003349646010000113
and
Figure GDA0003349646010000114
respectively representing the moment when the electric bus n is connected to and separated from the power grid;
equation (23) (24) is the available charge/discharge capacity constraint for the electric bus battery cluster, where CC(k.DELTA.t) and CD(k Δ t) respectively represents the available V2G charging capacity and the available V2G discharging capacity of the electric bus battery cluster at any time calculated according to the method in the step 3; pE(k Δ t) represents the total charge/discharge power of the electric bus battery cluster at any time, Pdw(k.DELTA.t) and Pup(k delta t) respectively represents the total descending reserve capacity and the ascending reserve capacity of the electric bus battery cluster at any time, and the calculation formulas of the three are as follows:
Figure GDA0003349646010000115
Figure GDA0003349646010000116
Figure GDA0003349646010000117
step 6: and solving the multi-objective optimization model of the electric bus battery cluster to obtain a charging/discharging plan of the electric bus battery cluster under the time scale of the day ahead.
The invention takes the charging and discharging behaviors of 16 buses at a bus charging station in a Suzhou industrial park in one day (6: 00-6: 00 the next day) as an example for testing.
In the embodiment, a BYD6121LGEV4 electric bus (10-41 seats of pure electric) is adopted; 4 departure times are set on the same day, the number of departure times of each shift is 2, 3, 2 and 1 in sequence, and 8 departure times are set; each bus needs about 1 hour for one-way operation, the time interval between each class is 30min, namely the bus dispatching and cluster optimizing time interval delta t is also 30 min. The bus-related core parameters are shown in table 1.
TABLE 1 electric bus Main parameters
Figure GDA0003349646010000118
Figure GDA0003349646010000121
During the test, local load data (as shown in fig. 3), real-time electricity prices, and up/down reserve capacity prices (as shown in fig. 4) are first obtained and input as input data into the MATLAB program. Secondly, a progressive bus management mode is established according to the bus running schedule, as shown in table 2.
TABLE 2 progressive bus management mode
Figure GDA0003349646010000122
Next, based on the progressive bus management mode shown in the above table, the rated power of the bus, the maximum and minimum SOC, and other parameters, the total charging/discharging capacity of the battery of the electric bus, which can be used as V2G, is calculated at any time. And then, based on the input data and the established management mode, establishing an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model, and establishing an electric bus battery cluster multi-objective optimization model on the basis. And finally, calling a CPLEX solver in an MATLAB program to solve the multi-target optimization model of the electric bus battery cluster to obtain a charging/discharging plan of the electric bus battery cluster under a time scale of the day and the year.
The embodiment illustrates the problem of inconsistent benefits among stakeholders when the battery of the electric bus participates in V2G, and shows the control result of the control method provided by the invention.
The test results of the examples show that:
the operation cost of the public transport company is $339.96 under the autonomous decision of the public transport company, and is $624.73 under the autonomous decision of the power grid, and the increase is 83.77 percent; conversely, the grid load peak-to-valley difference drops from 940.00kW to 70.96kW, which is a 92.45% reduction. Therefore, the problem of inconsistent benefits between the electric bus company and the power grid is proved, namely, when the two parties independently make decisions, the benefits of the other party are seriously lost.
After the multi-objective strategy optimization of the weighting method, the operation cost of a public transport company is $392.48, the load peak-valley difference is 177.23kW, the problem of benefit inconsistency of the public transport company and a power grid is effectively solved, and the effectiveness and the feasibility of the electric bus battery participation V2G control method considering multi-party benefits are demonstrated.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.

Claims (10)

1. A method for controlling the participation of a battery of an electric bus in V2G, which takes multi-party benefits into consideration, is characterized in that:
the method comprises the following steps:
step 1: acquiring day-ahead electricity price, load data and a bus running schedule;
step 2: establishing a progressive bus management mode based on a bus running schedule;
and step 3: calculating the available V2G charge/discharge capacity of the electric bus battery cluster at any moment based on the progressive bus management mode;
and 4, step 4: establishing an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model based on the day-ahead electricity price, load data and the available V2G charging/discharging capacity of the electric bus battery cluster at any moment;
and 5: establishing an electric bus battery cluster multi-objective optimization model based on an electric bus company operation cost minimization model and a power grid load peak-valley difference minimization model;
step 6: and solving the multi-objective optimization model of the electric bus battery cluster to obtain a charging/discharging plan of the electric bus battery cluster under the time scale of the day ahead.
2. The method of claim 1, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
step 2, establishing a progressive bus management mode based on the bus running schedule, specifically comprising the following steps:
determining 6 state time intervals delta T in the progressive bus management mode according to the departure time, the arrival charging time and the vehicle outage time of the electric bus in the electric bus running schedulei(i ∈ {1,2,. 6}), which are: the electric bus partially dispatches and partially participates in V2G; part of the bus operation is participated in, and part of the bus operation is participated in V2G; partial inbound charging, partial departure and partial participation in V2G; part of ginsengThe system and the bus operation partially participate in V2G; partial outage, partial participation V2G; all participate in V2G.
3. The method of claim 1, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
step 3, the charging/discharging capacity of the electric bus battery cluster at any moment can be V2G, and the calculation formula is as follows:
Figure FDA0003349637000000021
Figure FDA0003349637000000022
Figure FDA0003349637000000023
Figure FDA0003349637000000024
Figure FDA0003349637000000025
Figure FDA0003349637000000026
Figure FDA0003349637000000027
in the formula, CD(k Δ t) is the available V2G discharge capacity, CC(k Δ t) is the available V2G charge capacity; cD(k0Δ T) is Δ T1Available V2G discharge capacity at the start time; n is a radical ofkIs DeltaT1、ΔT3、ΔT5The corresponding bus shift of departure, arrival charging and stop at any time in the three state time periods; lambda [ alpha ]kThe number of buses for departure, arrival charging and stop of each class; delta CT(kiΔ t) (i belongs to {1,2,. and 6}) is the total capacity change amount of the electric bus battery cluster participating in V2G at any time; SOCresIs DeltaT3When each electric bus enters the station and is charged within the state time interval and the time difference is delta T5The average residual SOC value of the vehicle-mounted single batteries when each electric bus returns to the charging station after stopping in the state time period; Δ t is the minimum scheduling time interval; n is a radical ofv2g(k Δ T) represents Δ T1-ΔT6The total number of the electric buses participating in V2G at any k delta t moment in different state periods; cbatThe rated capacity of the single battery is stated in kWh; SOCminAnd SOCmaxRespectively, the lower limit and the upper limit of the state of charge SOC of the unit cell.
4. The method of claim 1, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
step 4, the operation cost minimization model of the electric bus company is as follows:
Figure FDA0003349637000000031
wherein, CCOMThe operating cost of the electric bus company participating in the standby service market in the day-ahead;
Figure FDA0003349637000000032
cost of electric energy interaction for the public transport company-the grid;
Figure FDA0003349637000000033
for public transport company asThe grid provides backup revenue for the up/down backup service;
Figure FDA0003349637000000034
the cost of battery loss caused by charging and discharging of each electric bus.
5. The method as claimed in claim 4, wherein the control method for battery participation V2G of electric bus includes:
cost of the bus company-grid for electric energy interaction
Figure FDA0003349637000000035
Standby revenue for public transport companies to provide up/down standby service to the grid
Figure FDA0003349637000000036
And the cost of battery loss caused by charging and discharging of each electric bus
Figure FDA0003349637000000037
The calculation formula is as follows:
Figure FDA0003349637000000038
Figure FDA0003349637000000039
Figure FDA00033496370000000310
in formula (9), rc(k Δ t) and rd(k delta t) respectively represents the charging/discharging real-time electricity price of the bus company at any time from the power grid, and the unit is $/kWh;
Figure FDA00033496370000000311
represents the charging power of the electric bus n at any moment,
Figure FDA00033496370000000312
the discharge power of the electric bus n at any moment is represented, and the unit is kW;
in the formula (10), gup(k.DELTA.t) and gdw(k Δ t) represents the rising and falling reserve capacity prices received by the public transport company from the power grid at any time, respectively, in units of $/kWh;
Figure FDA00033496370000000313
and
Figure FDA00033496370000000314
respectively representing the rising and falling standby capacities which can be provided by the electric buses at any time, wherein the unit is kW;
in formula (11), CdThe unit battery loss cost of the electric bus is expressed in $/kWh, and the calculation formula is as follows:
Figure FDA0003349637000000041
in the formula, CcThe investment cost of the battery is $; l iscThe number of times of recycling of the battery is set; DOD denotes depth of discharge.
6. The method of claim 1, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
step 4, the power grid load peak-valley difference minimization model is as follows:
min RLoad＝max[PL(kΔt)+PE(kΔt)]-min[PL(kΔt)+PE(kΔt)] (13)
in the formula, PL(k delta t) is any time in the local power grid control areaThe normal load of (2); pEAnd (k delta t) is the total charging/discharging power of the electric bus battery cluster at any moment.
7. The method of claim 1, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
step 5, establishing an electric bus battery cluster multi-objective optimization model based on the electric bus company operation cost minimization model and the power grid load peak-valley difference minimization model, specifically:
respectively aiming at the operation cost C by adopting a min-max standardized methodCOMAnd the peak-valley difference R of the load of the power gridLoadAnd carrying out normalization to obtain dimensionless variables C and R, thereby obtaining the multi-objective optimization model of the weighting method.
8. The method of claim 7, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
the multi-objective optimization model is as follows:
min(w1C+w2R) (14)
in the formula, w1And w2Respectively the weight value w of two targets of the operation cost of a public transport company and the load peak-valley difference of a power grid1+w2＝1。
9. The method of claim 8, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
the constraint conditions of the multi-objective optimization model are as follows:
Figure FDA0003349637000000042
Figure FDA0003349637000000051
Figure FDA0003349637000000052
Figure FDA0003349637000000053
Figure FDA0003349637000000054
Figure FDA0003349637000000055
Figure FDA0003349637000000056
Figure FDA0003349637000000057
Figure FDA0003349637000000058
Figure FDA0003349637000000059
wherein, the formulas (15) and (16) are the charging/discharging power constraints of a single electric bus,
Figure FDA00033496370000000514
the maximum charge/discharge power of the electric bus n, namely rated power, is represented by kW;
equations (17), (18), (19) are the charge/discharge power constraints for a single electric bus taking into account the reserve capacity;
equations (20), (21) and (22) are the single electric bus state of charge SOC constraints, wherein,
Figure FDA00033496370000000510
the battery SOC value represents the moment when the electric bus n is connected to the power grid;
Figure FDA00033496370000000511
andSOCrespectively is the lower limit and the upper limit of the SOC of the battery of the electric bus; k' is [1,24/Δ t ]]Any integer in between;
Figure FDA00033496370000000512
and
Figure FDA00033496370000000513
respectively representing the moment when the electric bus n is connected to and separated from the power grid;
equation (23) (24) is the available charge/discharge capacity constraint for the electric bus battery cluster, where CC(k.DELTA.t) and CD(k Δ t) represents the available V2G charging capacity and the available V2G discharging capacity of the electric bus battery cluster at any moment respectively; pE(k Δ t) represents the total charge/discharge power of the electric bus battery cluster at any time, Pdw(k.DELTA.t) and PupAnd (k delta t) respectively represents the total descending reserve capacity and the ascending reserve capacity of the electric bus battery cluster at any time.
10. The method of claim 9, wherein the V2G control method for battery participation of electric buses in multi-party interest comprises:
the total charging/discharging power P of the battery cluster of the electric bus at any timeE(k delta t), total rising reserve capacity P of electric bus battery cluster at any timedw(k Δ t) and reduced spare capacity Pup(k Δ t), which is calculated as follows:
Figure FDA0003349637000000061
Figure FDA0003349637000000062
Figure FDA0003349637000000063
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