CN107453381A - Electric automobile cluster power regulating method and system based on two benches cross-over control - Google Patents
Electric automobile cluster power regulating method and system based on two benches cross-over control Download PDFInfo
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- CN107453381A CN107453381A CN201710701781.0A CN201710701781A CN107453381A CN 107453381 A CN107453381 A CN 107453381A CN 201710701781 A CN201710701781 A CN 201710701781A CN 107453381 A CN107453381 A CN 107453381A
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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
- H02J3/28—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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- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/50—Controlling the sharing of the out-of-phase component
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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
- 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]
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The present invention relates to a kind of electric automobile cluster power regulating method and system based on two benches cross-over control, comprise the following steps：1) mixing of electric automobile cluster active reactive controls and pessimistic concurrency control is established, it is determined that carrying out the object function and its constraints of active reactive optimal control to electric automobile cluster；2) object function and its constraints that active optimization is carried out to electric automobile cluster are established；3) charge period of electric automobile cluster is divided into some Power Control periods；4) object function of active power controller is solved, obtains active power optimum results；5) object function and its constraints to the grid-connected idle work optimization of electric automobile cluster are established；6) object function of idle work optimization is solved, obtains wattles power economic equivalent result；7) repeat step 4)~6), active optimization and idle work optimization are carried out to electric automobile cluster within each Power Control period.It the composite can be widely applied to electric automobile cluster power adjusting.
Description
Technical field
The present invention relates to a kind of power regulating method and system of electric automobile cluster, and two ranks are based on especially with regard to one kind
The electric automobile cluster power regulating method and system of section cross-over control.
Background technology
In order to reduce the consumption to petroleum resources, alleviate problem of environmental pollution, effective method is being sought by each side, cleans
The use of the energy attracts widespread attention.Wherein, electric automobile replacing oil by electricity, " zero-emission " and " low noise can be realized
Sound ", conventional fuel oil automobile is gradually substituted, turn into the important means for solving energy resource consumption and environmental pollution.But electronic vapour
Car needs access power network to be charged, and the load of power network is on the one hand added, to power supply and demand balance and the safety of power system
Stability brings challenges；Another aspect electric automobile stops charging interval length, if can suitably be regulated and controled, has as movement
Battery energy storage participates in the potentiality of power network regulation.A wide range of popularization and construction of the electric automobile charging and conversion electric facility in power distribution network are electricity
Electrical automobile charge control provides the foundation, and power electronic equipment is as between electric automobile energy-storage battery and distribution network line
Interface, it ensure that rapidity and the flexibility of charging electric vehicle Power Control.Meanwhile with the construction of intelligent distribution system,
User's request response technology is by its bidirectional communication network, advanced measurement technology and advanced DSS, to user power utilization
Model is adjusted, and directly management or guiding user changes itself electric energy consumption behavior, promotes the optimization balance of supply and demand both sides, real
Show reliable power network, safety, economy, efficient, environment-friendly and safe to use Effec-tive Function.To the electronic of extensive access power network
Automobile carries out a kind of important control device and resource form that charge power control is user's request response technology, electric automobile collection
The grid-connected battery energy management of group also can be considered a kind of virtual energy storage system, stabilizes distribution type renewable energy access power network and causes
Power swing, further increase the value in terms of economy and environment caused by clean energy resource.Therefore, how meet it is electronic
It is the controllable resources that power network provides that charging electric vehicle energy is made full use of while user vehicle demand, how for electronic vapour
The characteristics of car cluster is grid-connected lifting regulation and control level and economic and environmental benefit, intelligence will be turned into and match somebody with somebody electricity consumption and electric automobile cutting-in control
The middle key issue for needing to solve.
Nowadays, having been working on how adjusting the charge power of electric automobile both at home and abroad from quantitative technical standpoint research is
Power network provides a variety of assistant services.Such as：Propose the evaluation method of charging electric vehicle load and to power network quality of power supply shadow
Loud analysis and assessment method, establish the electric automobile cutting-in control model comprising automobile user and power distribution network framework；Will
The controller of electric automobile cluster interacts as temporary location with power network, proposes multilayer control structure to reduce control difficulty and lead to
Letter burden；The energy-optimised scheduling model using electric automobile charge-discharge electric power as control variable is established, using intelligent optimization algorithm
The Optimal Scheduling of multiple target more periods is solved, peak load shifting is realized by the regulation to electric automobile power, reduction is matched somebody with somebody
Network operation cost, improve the economic and environmental benefits such as new energy consumption.But electric automobile individual capacity is small and widely distributed, user
Demand is different, extensive electric automobile centralized optimization call duration time length, calculates magnanimity, and existing research still lacks to electronic vapour
The grid-connected effective solution of modeling and centralized Control difficult problem completely of car cluster.
The content of the invention
In view of the above-mentioned problems, it is an object of the invention to provide a kind of electric automobile cluster work(based on two benches cross-over control
Rate adjusting method and system, the quick control to measuring electric automobile cluster scattered greatly is realized by two benches cross-over control mode
System and global optimization, solve the power quality problem that the unordered charge-carrying belt of a large amount of electric automobiles comes, and idle branch is provided for power network
Hold.
To achieve the above object, the present invention takes following technical scheme：A kind of electronic vapour based on two benches cross-over control
Car cluster power regulating method, it is characterised in that comprise the following steps：1) the mixing control of electric automobile cluster active reactive is established
And pessimistic concurrency control, and determined according to the model to carry out electric automobile cluster the object function and its about of active reactive optimal control
Beam condition；2) based on the object function that active reactive optimal control is carried out to electric automobile cluster, establish to electric automobile cluster
Carry out the object function and its constraints of active optimization control；3) charge period of electric automobile cluster is divided into some EV
Power Control period TC, every EV Power Control periods TC are divided into EV charge powers optimization period TP and EV the Reactive-power control period again
Two stages of TQ；4) current EV charge powers optimization period TP in, according to the active optimization of foundation control object function and
Its constraints, scheduling is optimized to the active power of all vehicles in electric automobile cluster, obtained in electric automobile cluster
The active power regulation result of each electric automobile；5) object function for carrying out idle work optimization grid-connected to electric automobile cluster is established,
And according in the electric automobile cluster obtained in charging electric vehicle facility operation characteristic and step 4) each electric automobile it is active
Power adjusting result, establish the Reactive-power control constraints of decoupled active and reactive degree；6) in current EV Reactive-power controls period TQ,
According to the object function of the idle work optimization of foundation and Reactive-power control constraints, idle work optimization is carried out to electric automobile cluster, obtained
The reactive power regulation result of each electric automobile in electric automobile cluster；7) repeat step 4)~6), in each EV charge powers
Optimize in period TP and active optimization is carried out to electric automobile cluster, in each EV Reactive-power controls period TQ, to electric automobile cluster
Idle work optimization is carried out, until all EV Power Controls period TC of electric automobile cluster terminate.
In the step 1), the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and to electric automobile collection
Group carries out the object function of active reactive optimal control and its method for building up of constraints, comprises the following steps：1.1) basis
Automobile user demand and power grid user side apparatus power adjusting target, establish electric automobile cluster and pessimistic concurrency control；1.2) it is sharp
With the Reactive-power control ability of electric vehicle charge interface power electronic equipment, add in the electric automobile cluster and pessimistic concurrency control of foundation
Enter electric automobile cluster no-power compensation function, obtain the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control；1.3) root
According to the mixing control of the electric automobile cluster active reactive and pessimistic concurrency control of foundation, obtain carrying out active reactive to electric automobile cluster
The object function of optimal control；1.4) point according to topological structure of electric and typical load curve combination electric automobile in power network
Cloth situation calculates the operation of power networks state of extensive electric automobile access, and then obtains the object function of active reactive optimal control
The operation of power networks constraint that need to meet and grid power equilibrium constraint；1.5) according to electric automobile vehicle, battery capacity, user
Down time and electrically-charging equipment rated capacity parameter, calculate batteries of electric automobile state, controllable range of capacity and electric automobile and fill
Electric load, and then the batteries of electric automobile energy storage constraint and charging that the need for obtaining the object function of active reactive optimal control meet
Power constraints.
In the step 1), the object function to the progress active reactive optimal control of electric automobile cluster is：
In formula, RijThe impedance of circuit between i-th of node of power network and j-th of node；N is grid nodes number；Iij(t)
For the line current of t；F (X) is total network loss in the T periods；X is optimized variable and system state variables, and：
In formula,For the charge power of electric automobile t, namely active power；Carried for electric automobile
The reactive power regulated quantity of confession；K is the numbering of the electric automobile in electric automobile cluster；
The bound for objective function of the active reactive optimal control includes operation of power networks constraints, grid power
Equilibrium constraint and batteries of electric automobile energy storage constraint and charge power constraints；
Wherein, the operation of power networks constraints is：
Vmin≤|Vi(t)|≤Vmaxi∈N；
In formula, Vi(t) for node i voltage amplitude, VmaxAnd VminThe respectively upper and lower limit of voltage deviation；Imax(t)
Limited for capacity of trunk；
The grid power equilibrium constraint is：
In formula,WithRespectively generated output；WithRespectively load active power and idle
Power；ViAnd δ (t)i(t) be respectively node i voltage amplitude and phase angle；VjAnd δ (t)j(t) it is respectively and i adjacent nodes j
Voltage magnitude and phase angle；YijAnd θijThe respectively amplitude and phase angle of bus admittance matrix；
The batteries of electric automobile energy storage constraint and charge power constraints are respectively：
In formula, CbatFor battery capacity, CeffFor the charge efficiency of electrically-charging equipment；It is kth electricity at access node i
The initial cell energy storage state of electrical automobile；SOCminAnd SOCmaxBattery energy storage is upper and lower during to be completed by charging electric vehicle
Limit；SOCi,k(t) it is the battery electric quantity of kth electric automobile at access node i.
In the step 2), the object function of active power controller and its building for constraints are carried out to electric automobile cluster
Cube method, comprise the following steps：
2.1) according to power network basic load, charging electric vehicle load and distributed power generation, electric automobile cluster is entered
The object function of row active reactive Power Control carries out equivalent-simplification, obtains carrying out active optimization control to electric automobile cluster
Object function：
In formula, F1(X) it is the net load quadratic sum comprising electric automobile and distributed power generation； Respectively
Access node i load and distributed power generation；For the charging load of kth electric automobile；KiAt access node i
Electric automobile quantity；
2.2) according to the rated output power of charging electric vehicle facility, the charge power and grid requirements of different automobile types
Access load range, obtain the active power regulation range constraint condition that need to meet of object function of active optimization control：
In formula,WithRespectively the rated output power of charging electric vehicle facility and different automobile types are set most
Big charge power；Pi,minAnd Pi,maxThe load range that respectively electric automobile cluster access point is set according to grid requirements.
In the step 4), the object function and its constraints that are controlled according to the active optimization of foundation, to electric automobile
The method that the charge power of all vehicles optimizes scheduling in cluster, comprises the following steps：4.1) by the active optimization of foundation
The object function of control is decomposed, and obtains the upper strata optimization aim for realizing total charging Load Regulation in dispatching of power netwoks aspect
Function, and for tracking the object function for the lower floor's tracing control for adjusting each charging electric vehicle power；4.2) according to upper
Layer optimization object function and grid load curve, carry out upper strata and optimize to obtain total charging load target of electric automobile cluster；
4.3) according to total charging load target of the electric automobile cluster obtained in lower floor's tracing control object function and step 4.2),
Active power regulation is carried out to each electric automobile in electric automobile cluster using scattered optimization method, obtains electric automobile cluster
Interior each electric automobile meets the active power regulation result that upper strata is always charged under load target in charge period.
In the step 4.1), the upper strata optimization object function is：
In formula, G (Y) is minimum load fluctuation；Y is optimized variableThat is electric automobile cluster always charges load
Desired value；For meter and the load average value of charging electric vehicle；For the charge power of kth electric automobile；For
Network load, and：
The object function of lower floor's tracing control is：
In formula, H (Z) is the desired value of total charging loadWith the actual charge power of electric automobileBetween
Difference；Z is optimized variable
In the step 4.3), according to lower floor's tracing control object function and total charging load mesh of electric automobile cluster
Mark, the method for being carried out active power regulation to electric automobile cluster using scattered optimization method, is comprised the following steps：
When total charging load target of electric automobile cluster 4.3.1) being evenly distributed into the charging of each electric automobile setting
Section, and according to the bound constraints of active power, the initial value of each charging electric vehicle power curve is calculated：
4.3.2) according to the initial value of each charging electric vehicle power curve, calculate each electronic in current electric automobile cluster
Difference between automobile charge power summation and total charging load desired value：
In formula, m represents iterations；The charge power of the kth electric automobile obtained for last iteration；Kv=
Ki× N is electric automobile sum；
4.3.3) according to step 4.3.2) in obtained difference, to the charge power of each electric automobile in electric automobile cluster
Curve is optimized respectively, and its charge power curve is updated according to the charge power optimized variable of each electric automobile；
The object function optimized to the charge power of each electric automobile in electric automobile cluster is：
In formula,The kth charging electric vehicle power optimization variable tried to achieve for current iteration, andFor
4.3.4 after) judgement updates in electric automobile cluster between each charge power summation and total charging load desired value
Whether difference meets the condition of convergence, i.e. whether difference is less than the boundary value of setting or reaches the maximum iteration of setting：If no
Meet, then return to step 4.3.2), carry out next iteration；If satisfied, then iteration terminates, output result.
In the step 5), the object function of the grid-connected idle work optimization of electric automobile cluster and building for Reactive-power control constraints
Cube method, comprise the following steps：5.1) according to the charging electric vehicle facility Reactive-power control amount in idle work optimization period TQ and connecing
Enter the operation of power networks state variable of charging electric vehicle load, establish the object function of the grid-connected idle work optimization of electric automobile；5.2)
According to the chargometer of each electric automobile in the electric automobile cluster obtained in charging electric vehicle facility operation characteristic and step 4)
Draw, establish the Reactive-power control constraints that the object function of idle work optimization need to meet；5.3) according to the object function peace treaty of foundation
Beam condition carries out idle work optimization to electric automobile cluster, obtains the reactive power regulation knot of each electric automobile in electric automobile cluster
Fruit.
In the step 5), the object function of the idle work optimization of foundation is：
In formula, F2(X) it is total network loss of t, optimized variable X is the reactive power that electric automobile provides
The constraints of the idle work optimization is：
In formula,For the rated capacity of charging electric vehicle facility；Cos θ represent minimum power during charging equipment work
Factor；The t active power optimal solution provided for first stage control, and
In formula, PvmaxFor the active power maximum of electric automobile.
A kind of electric automobile cluster power regulating system based on two benches cross-over control suitable for methods described, it is special
Sign is：It includes：
Grid-connected model construction module, for building the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and root
Obtain carrying out electric automobile cluster the object function and its constraints of active reactive optimal control according to described and pessimistic concurrency control；
Active optimization object function builds module, for carrying out the mesh of active reactive optimal control based on electric automobile cluster
Scalar functions, the object function and its constraints that active optimization is carried out to electric automobile cluster is calculated；
Charge period division module, include active power for the charge period of electric automobile cluster to be divided into several
Adjust the period and the reactive power regulation period two adjusts the charging electric vehicle power optimization period of period；
Active power optimization module, within each active power regulation period, having according to electric automobile cluster
The object function and its constraints of work(optimization, active power regulation is carried out to electric automobile cluster；
Idle work optimization object function builds module, carries out the object function of idle work optimization to electric automobile cluster for establishing
And its constraints；
Wattles power economic equivalent module, within each reactive power regulation period, nothing to be carried out according to electric automobile cluster
The object function and its constraints of work(optimization, reactive power regulation is carried out to electric automobile cluster.
For the present invention due to taking above technical scheme, it has advantages below：1 is of the invention by the active nothing of electric automobile cluster
Work(mixing control is decomposed into active power optimization and idle work optimization, and active power controller is realized to match with power network local load,
Peak load shifting is realized under conditions of user's request is met, ensures the economic security operation of power network；Reactive Power Control it is main
Target is voltage and reactive power optimization, considers that electrically-charging equipment regulating power is realized on the basis of first stage active optimization is realized
Idle work optimization, control complexity is effectively reduced by two benches cross-over control mode.2nd, the present invention in the first stage active
It is the Power Control period, equivalent with to active reactive Hybrid Control Model simplify according to charging load, for electronic in cluster
Automobile charging load management establishes electric automobile cluster and pessimistic concurrency control, avoids the related complexity of topological structure of electric modeling
Degree.3rd, the present invention is in the Reactive power control of second stage, by avoiding multi-period Optimized model to electric motor car cluster
Related complexity.It is that the reality of electric automobile cluster cutting-in control should so as to significantly reduce control difficulty and communications burden
With providing effective means.Thus, the present invention can be widely applied to the grid-connected Power Control field of electric automobile cluster.
Brief description of the drawings
Fig. 1 is the charge power adjusting method flow chart of the electric automobile cluster of the invention based on two benches cross-over control；
Fig. 2 is the schematic diagram of electric automobile active reactive mixing regulation of the present invention；
Fig. 3 (a) is the schematic diagram of electric automobile cluster charging Load Regulation of the present invention；
Fig. 3 (b) is the schematic diagram of electric automobile cluster Reactive-power control of the present invention；
Fig. 4 is charging electric vehicle power adjusting of the present invention and energy state schematic diagram；
Fig. 5 is the line loss schematic diagram of the grid-connected power adjusting of electric automobile cluster of the present invention；
Fig. 6 is the voltage deviation schematic diagram of the grid-connected power adjusting of electric automobile cluster of the present invention.
Embodiment
The present invention is described in detail with reference to the accompanying drawings and examples.
A kind of as shown in figure 1, electric automobile cluster power adjusting side based on two benches cross-over control proposed by the present invention
Method, comprise the following steps：
1) mixing of electric automobile cluster active reactive controls and pessimistic concurrency control is established, and is determined according to the model to electronic vapour
Car cluster carries out the object function and its constraints of active reactive optimal control；
2) object function for the active reactive optimal control being based in step 1), establish active to the progress of electric automobile cluster
The object function and its constraints of optimal control；
3) charge period of electric automobile cluster is divided into some EV (electric automobile) Power Control period TC, every EV
Power Control period TC is divided into EV charge powers optimization two stages of period TP and EV Reactive-power control period TQ again；
4) in first stage, i.e., within current EV charge powers optimization period TP, controlled according to the active optimization of foundation
Object function and its constraints, scheduling is optimized to the active power of all vehicles in electric automobile cluster, obtained electronic
The active power regulation result of each electric automobile in automobile cluster, i.e., the charging plan of each electric automobile；
5) object function for carrying out idle work optimization grid-connected to electric automobile cluster is established, and according to charging electric vehicle facility
The active power regulation result of each electric automobile, establishes active nothing in the electric automobile cluster obtained in operation characteristic and step 4)
The Reactive-power control constraints of work(decoupling degree；
6) in second stage, i.e., in current EV Reactive-power controls period TQ, according to the object function of the idle work optimization of foundation
And Reactive-power control constraints, idle work optimization is carried out to power network automobile cluster, obtains each electric automobile in electric automobile cluster
Reactive power adjusts result；
7) repeat step 4)~6), electric automobile cluster is carried out within each EV charge powers optimization period TP active excellent
Change, in EV Reactive-power control periods TQ, idle work optimization is carried out to electric automobile cluster, until all EV work(of electric automobile cluster
Rate control time TC terminates.
Above-mentioned steps 1) in, the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and to electric automobile collection
Group carries out the object function of active reactive optimal control and its method for building up of constraints, comprises the following steps：
1.1) according to automobile user demand and power grid user side apparatus power adjusting target, electric automobile cluster is established
And pessimistic concurrency control.
1.2) as shown in Fig. 2 using electric vehicle charge interface power electronic equipment Reactive-power control ability, in foundation
Electric automobile cluster no-power compensation function is added in electric automobile cluster and pessimistic concurrency control, electric automobile cluster active reactive is obtained and mixes
Close control and pessimistic concurrency control.
1.3) control and pessimistic concurrency control is mixed according to the electric automobile cluster active reactive of foundation, obtained to electric automobile collection
Group carries out the object function of active reactive optimal control.
The target that active reactive optimal control is carried out to electric automobile cluster be make the charging load of electric automobile cluster with
Grid load curve matches, and realizes the effect of peak load shifting, while provides no-power compensation function and further improve power supply quality
It is lost with distribution network line is reduced, thus, the object function for obtaining carrying out active reactive optimal control is：
In formula, RijThe impedance of circuit between i-th of node of power network and j-th of node；N is grid nodes number；Iij(t)
For the line current of t；F (X) is total network loss in the T periods；X is optimized variable and system state variables, and：
In formula,For the charge power of electric automobile t, namely active power；Carried for electric automobile
The reactive power regulated quantity of confession；K represents the numbering of the electric automobile in electric automobile cluster.
1.4) calculated according to the distribution situation of topological structure of electric and typical load curve combination electric automobile in power network
The operation of power networks state of extensive electric automobile access, and then the electricity that the object function for obtaining active reactive optimal control need to meet
Network operation constrains and grid power equilibrium constraint.
Wherein, operation of power networks constraints is：
Vmin≤|Vi(t)|≤Vmax i∈N (3)
In formula, Vi(t) for node i voltage amplitude, VmaxAnd VminThe respectively upper and lower limit of voltage deviation；Imax(t)
Limited for capacity of trunk.
Grid power equilibrium constraint is：
In formula,WithRespectively generated output；WithRespectively load active power and idle
Power；ViAnd δ (t)i(t) be respectively node i voltage amplitude and phase angle；VjAnd δ (t)j(t) it is respectively and i adjacent nodes j
Voltage magnitude and phase angle；YijAnd θijThe respectively amplitude and phase angle of bus admittance matrix.
1.5) according to electric automobile vehicle, battery capacity, the parameter meter such as user's down time and electrically-charging equipment rated capacity
Batteries of electric automobile state, controllable range of capacity and charging electric vehicle load are calculated, and then obtains active reactive optimal control
The batteries of electric automobile energy storage constraint and charge power constraints that the need of object function meet.
Wherein, batteries of electric automobile energy storage constraint and charge power constraints are respectively：
In formula, CbatFor battery capacity, CeffFor the charge efficiency of electrically-charging equipment；It is kth electricity at access node i
The initial cell energy storage state of electrical automobile；SOCi,k(t) it is the battery electric quantity of kth electric automobile at access node i；
SOCminAnd SOCmaxThe bound of battery energy storage during to be completed by charging electric vehicle, be typically set by the user the off-network time and from
SOC limitations during net, additionally need and ensure that battery energy storage is without departing from battery capacity scope at any time.Charge power it is adjustable
Adjusting range is limited by the rated capacity of charging equipment：
In formula, PfminAnd PfmaxFor the bound of charging equipment adjustable extent, and present invention assumes that charging equipment only has
Charge function, do not consider that bidirectional power is adjusted.
Above-mentioned steps 2) in, the object function of active power controller and its building for constraints are carried out to electric automobile cluster
Cube method, comprise the following steps：
2.1), will be to electric automobile cluster according to power network basic load, charging electric vehicle load and distributed power generation
The object function for carrying out active reactive Power Control carries out equivalent-simplification, obtains carrying out active optimization control to electric automobile cluster
Object function.
The object function of active reactive optimal control is carried out in reality to electric automobile cluster by being established in step 1)
Difficulty is very big when border calculates, so the present invention carries out equivalent-simplification to it.According to the radial topological structure of low and medium voltage distribution network and
Circuit R/X realizes the target of reduction network loss by adjusting active power distribution, can be equivalent to reduce load ripple than high characteristic
Dynamic, real power control reaches by making charging electric vehicle load and grid load curve match and reduces power distribution network in step 1)
The target of line loss.
To realize the quick control to large number of electric automobile, charging load and the load curve phase of access area are considered
Matching, Optimal Operation Model does not include topological structure of electric, using day part charging electric vehicle power as optimized variable, realizes flat
The target of slipstream test curve：By the reasonable layout of electric automobile cluster charging load, reduce bearing for the power network in charge period
Lotus changes, and reduces peak-valley difference, improves operation of power networks condition, thus the object function of active power controller is：
In formula, F1(X) it is the net load quadratic sum comprising electric automobile and distributed power generation, reflects load fluctuation feelings
Condition； Respectively access node i load and distributed power generation；Charging for kth electric automobile is born
Lotus；KiFor the electric automobile quantity at access node i.
2.2) according to the rated output power of charging electric vehicle facility, the charge power and grid requirements of different automobile types
Access load range, obtain the active power regulation range constraint condition that need to meet of object function of active optimization control：
In formula,WithRespectively the rated output power of charging electric vehicle facility and different automobile types are set most
Big charge power；Pi,minAnd Pi,maxThe load range that respectively electric automobile cluster access point is set according to grid requirements.
Above-mentioned steps 4) in, according to the object function and its constraints of the active power controller of foundation, to electric automobile
The method that the charge power of all vehicles optimizes scheduling in cluster, comprises the following steps：
4.1) object function that the active optimization established in step 2) controls is decomposed, obtains being used in dispatching of power netwoks
Aspect realizes the upper strata optimization object function of total charging Load Regulation, and adjusts each charging electric vehicle power for tracking
Lower floor's tracing control object function.
To make calculating more faster, the present invention is decomposed the object function of active optimization control, and upper strata optimization is real
Load fluctuation is now minimized, lower floor's tracking is realizedThen dual-layer optimization result can with it is above-mentioned active excellent
Change equivalent, and its constraints is consistent with the bound for objective function of active power controller in step 3).
Wherein, the object function of upper strata optimization is：
In formula, G (Y) is minimum load fluctuation；Y is optimized variableRepresent the electronic vapour of participation dispatching of power netwoks
Car cluster always charges the desired value of load；For meter and the load average value of charging electric vehicle；For kth electric automobile
Charge power；For network load, the summation for accessing load and distributed power source in above-mentioned formula (11) is represented, i.e.,：
The object function of lower floor's tracing control is：
In formula, H (Z) is the desired value of total charging loadWith the actual charge power of electric automobileBetween
Difference；Z is optimized variable
4.2) according to upper strata optimization object function (14) and grid load curve, carry out upper strata and optimize to obtain electric automobile
Total charging load target of cluster
4.3) according to total charging of the electric automobile cluster obtained in lower floor's tracing control object function and step 4.2)
Load targetActive power regulation is carried out to electric automobile cluster using scattered optimization method, obtains electric automobile collection
Each electric automobile meets the active power regulation result that upper strata is always charged under load target in charge period in group.
Above-mentioned steps 4.3) in, due to optimized variable in the object function of lower floor's tracking shown in formula (17)Comprising
Charge power of all electric automobiles in day part, is designated as PEV,k(t)=[PEV,1(t),…,PEV,k(t),…PEV,Ki×N(t)
]T, although the problem is convex double optimization problem, but when electric automobile quantity is larger, centralized optimization method solves difficult.
To reduce computation complexity, using scattered optimization method, the characteristics of weak coupling, is had according to the optimization problem, i.e., each electronic vapour
Car optimized variable PEV,k(t) decouple in constraint, only coupled in object function each other, itself can be separately optimized in each electric automobile
Charge power, while mutually coordinate with electric automobile cluster charge power general objective, centralized optimization identical reached by iteration
Effect, each electric automobile of each iterative PEV,k(t) the small-scale optimization problem formed with coordination information, when reducing calculating
Between.
According to total charging load target of lower floor's tracing control object function and electric automobile cluster, using scattered optimization
The method that method carries out active power regulation to electric automobile cluster, comprises the following steps：
When total charging load target of electric automobile cluster 4.3.1) being evenly distributed into the charging of each electric automobile setting
Section, and according to the bound constraints of active power, the initial value of each charging electric vehicle power curve is calculated：
4.3.2) according to the initial value of each charging electric vehicle power curve, calculate each electronic in current electric automobile cluster
Difference between automobile charge power summation and total charging load desired value：
In formula, m represents iterations；The charge power of the kth electric automobile obtained for last iteration；Kv=
Ki× N is electric automobile sum, and the formula is planned to obtain and day part charge power using each car charging of last iteration
Difference
4.3.3) according to step 4.3.2) in obtained difference, to the charge power of each electric automobile in electric automobile cluster
Curve is optimized respectively, and its charge power curve is updated according to the charge power optimized variable of each electric automobile.
The object function optimized to the charge power of each electric automobile in electric automobile cluster is：
In formula,The kth charging electric vehicle power optimization variable tried to achieve for current iteration, andFor
4.3.4 after) judgement updates in electric automobile cluster between each charge power summation and total charging load desired value
Whether difference meets the condition of convergence, i.e. whether difference is less than the boundary value of setting or reaches the maximum iteration of setting.If no
Meet, then return to step 4.3.2), carry out next iteration；If satisfied, then iteration terminates, output result.
Above-mentioned steps 5) in, the object function of the grid-connected idle work optimization of electric automobile cluster and building for Reactive-power control constraints
Cube method, comprise the following steps：
5.1) filled according to the charging electric vehicle facility Reactive-power control amount in idle work optimization period TQ and access electric automobile
The operation of power networks state variable of electric load, establish the object function of the grid-connected idle work optimization of electric automobile.
The Reactive-power control ability possessed according to charging electric vehicle facility, using the reactive power provided at access point to be excellent
Change variable, reduce grid net loss.Idle work optimization is the second stage of above-mentioned two benches active reactive cross-over control, electronic in implementation
On the basis of automobile charge power Optimized Operation, reactive power control is carried out within each period, optimization problem only considers single
Period is to simplify solution procedure.The object function of the grid-connected idle work optimization of electric automobile is：
In formula, F2(X) it is total network loss of t, optimized variable X is the reactive power that electric automobile provides
5.2) according to each electronic in the electric automobile cluster obtained in charging electric vehicle facility operation characteristic and step 4)
The charging plan of automobile, establish the Reactive-power control constraints that the object function of idle work optimization need to meet.
Constraints is the degree of coupling constraint of electric automobile active reactive mixing control, is shown below：
In formula,For the rated capacity of charging electric vehicle facility, when representing to provide active power and reactive power simultaneously
The capacity-constrained of power device.When considering running wastage, formula (23) is converted to：
In formula, SR,kLimited for charging equipment of electric automobile working capacity；For the running wastage of power device；
T charge power optimal solution is provided for first stage control, and
In formula, PvmaxFor the active power maximum of electric automobile, set no more than electric automobile and electrically-charging equipment both sides
Specified charge power, in two-stage control implementation procedure, determined by the optimal solution of first stage.
In formula, cos θ represent minimum power factor during charging equipment work, represent output work of the power network to grid-connection device
Rate limits.When considering running wastage, formula (26) is converted to following formula：
In formula, tan θ are that the power factor of grid-connection device constrains；For the running wastage of power device.
5.3) idle work optimization is carried out to electric automobile cluster according to the object function of foundation and constraints, obtains electronic vapour
The reactive power regulation result of each electric automobile in car cluster.
Electric automobile cluster power regulating method based on above-mentioned two benches cross-over control, the present invention also propose a kind of be applicable
In the electric automobile cluster power regulating system based on two benches cross-over control of this method, it includes：
Grid-connected model construction module, for building the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and root
According to this, simultaneously pessimistic concurrency control obtains the object function and its constraints to the progress active reactive optimal control of electric automobile cluster；
Active optimization object function builds module, for carrying out the mesh of active reactive optimal control based on electric automobile cluster
Scalar functions, the object function and its constraints that active optimization is carried out to electric automobile cluster is calculated；
Charge period division module, include active power for the charge period of electric automobile cluster to be divided into several
Adjust the period and the reactive power regulation period two adjusts the charging electric vehicle power optimization period of period；
Active power optimization module, within each active power regulation period, having according to electric automobile cluster
The object function and its constraints of work(optimization, active power regulation is carried out to electric automobile cluster；
Idle work optimization object function builds module, carries out the object function of idle work optimization to electric automobile cluster for establishing
And its constraints；
Wattles power economic equivalent module, within each reactive power regulation period, nothing to be carried out according to electric automobile cluster
The object function and its constraints of work(optimization, reactive power regulation is carried out to electric automobile cluster.Below with specific example
To verify the feasibility provided by the invention based on two benches cross-over control electric automobile cluster power conditioning technology.Choose 33 sections
Point typical distribution net simultaneously accesses polytype electric automobile in different nodes, and it is 300 to set grid-connected electric automobile sum, wherein
Each half of the two kinds of electric automobiles of Tesla Roadster and Nissan Leaf, it is randomly distributed in 6 nodes and is obtained from feeder line
Take charge power and reactive power is provided and carry out reactive power optimization.Set charging electric vehicle scene to charge as family, in evening
Electric automobile is according to the berthing time of user and departure time and electricity in the upper 6 points charge periods to 6: 12 hours of morning
Pond state computation charging electric vehicle load is about the 10%~15% of total load, under unordered charge condition, this part electricity
Electrical automobile charging load will be with basic load curve combining, and peak value and power supply quality to power network produce harmful effect.
It is the basic load that electric automobile accesses 33 Node power distribution systems in the present embodiment as shown in Fig. 3 (a), Fig. 3 (b),
The data fit normal distributions such as the networking of electric automobile, off-network time, the energy content of battery consumption that distance travelled is brought are set, it is electronic
Automobile charging load is about 12.5% by calculating accounting.In the case where not controlling charge condition, electric automobile access is charged, and gained fills
Electric load curve is compared with charge power control situation.The distribution network of electric automobile access is powered by Bulk Supply Substation, upper strata
Power network is conveyed to the active power of distribution by Bulk Supply Substation, shown in reactive power such as accompanying drawing 3 (b).A large amount of charging electric vehicles
Load increases the peak load of power network, and by the Optimized Operation to electric automobile cluster rechargeable energy, peak load reduces
24.8%, the charging load of electric automobile elapses the underload period backward, realizes the target of smooth load curve.Electric automobile
Cluster provides Reactive-power control at access point, further optimize distribution power distribution, Bulk Supply Substation conveying reactive power and
Apparent energy is all accordingly reduced, and is advantageous to reduce the operating cost of power network, improves the economic effect of charging electric vehicle Power Control
Benefit.It is respectively 3.7MWh and 2.9MWh using total network loss before and after the electric automobile cluster power adjusting, network loss reduces 21%,
Realize the optimization aim for minimizing loss.
As shown in figure 4, charge power regulation and energy state schematic diagram are carried out to electric automobile cluster for the present invention.In figure
The charging plan of each electric automobile provides by power control algorithm, different according to the parameter of each electric automobile, is entirely filling
Charging plan and energy content of battery SOC changes in the electric period, ensure that all vehicles are satisfied by grid-connected time and the electricity of user's setting
The demands such as pond SOC.
As shown in Figure 5, Figure 6, it is the voltage deviation schematic diagram of the grid-connected power adjusting of electric automobile cluster.Can from figure
Go out, the application of electric automobile cluster power control techniques significantly reduces voltage deviation and line loss, and charging electric vehicle is born
Voltage deviation is limited within 10% after lotus introduces power network, and peak line loss reduces 37.4% so that node voltage and line
Road electric current is not out-of-limit, ensures the safe and stable operation and power supply quality of power network.
The various embodiments described above are merely to illustrate the present invention, wherein the structure of each part, connected mode and manufacture craft etc. are all
It can be varied from, every equivalents carried out on the basis of technical solution of the present invention and improvement, should not exclude
Outside protection scope of the present invention.
Claims (10)
1. a kind of electric automobile cluster power regulating method based on two benches cross-over control, it is characterised in that including following step
Suddenly：
1) mixing of electric automobile cluster active reactive controls and pessimistic concurrency control is established, and is determined according to the model to electric automobile collection
Group carries out the object function and its constraints of active reactive optimal control；
2) based on the object function that active reactive optimal control is carried out to electric automobile cluster, establish and electric automobile cluster is carried out
The object function and its constraints of active optimization control；
3) charge period of electric automobile cluster is divided into some EV Power Controls period TC, every EV Power Control periods TC
It is divided into EV charge powers optimization two stages of period TP and EV Reactive-power control period TQ again；
4) within current EV charge powers optimization period TP, the object function and its constraint bar that are controlled according to the active optimization of foundation
Part, scheduling is optimized to the active power of all vehicles in electric automobile cluster, obtain each electronic vapour in electric automobile cluster
The active power regulation result of car；
5) object function for carrying out idle work optimization grid-connected to electric automobile cluster is established, and according to charging electric vehicle facility operation
The active power regulation result of each electric automobile, establishes active reactive solution in the electric automobile cluster obtained in characteristic and step 4)
The Reactive-power control constraints of coupling degree；
6) in current EV Reactive-power controls period TQ, bar is constrained according to the object function of the idle work optimization of foundation and Reactive-power control
Part, idle work optimization is carried out to electric automobile cluster, obtain the reactive power regulation result of each electric automobile in electric automobile cluster；
7) repeat step 4)~6), active optimization is carried out to electric automobile cluster within each EV charge powers optimization period TP,
In each EV Reactive-power controls period TQ, idle work optimization is carried out to electric automobile cluster, until all EV power of electric automobile cluster
Control time TC terminates.
2. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 1), the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and electric automobile cluster is carried out
The object function of active reactive optimal control and its method for building up of constraints, comprise the following steps：
1.1) according to automobile user demand and power grid user side apparatus power adjusting target, it is grid-connected to establish electric automobile cluster
Model；
1.2) utilize electric vehicle charge interface power electronic equipment Reactive-power control ability, foundation electric automobile cluster simultaneously
Electric automobile cluster no-power compensation function is added in pessimistic concurrency control, obtains the grid-connected mould of electric automobile cluster active reactive mixing control
Type；
1.3) control and pessimistic concurrency control is mixed according to the electric automobile cluster active reactive of foundation, obtains entering electric automobile cluster
The object function of row active reactive optimal control；
1.4) big rule are calculated according to the distribution situation of topological structure of electric and typical load curve combination electric automobile in power network
The operation of power networks state of mould electric automobile access, and then the power network fortune that the object function for obtaining active reactive optimal control need to meet
Row constraint and grid power equilibrium constraint；
1.5) according to electric automobile vehicle, battery capacity, user's down time and electrically-charging equipment rated capacity parameter, calculate electronic
Automobile batteries state, controllable range of capacity and charging electric vehicle load, and then obtain the target letter of active reactive optimal control
The batteries of electric automobile energy storage constraint and charge power constraints that several need meet.
3. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 1), the object function to the progress active reactive optimal control of electric automobile cluster is：
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In formula, RijThe impedance of circuit between i-th of node of power network and j-th of node；N is grid nodes number；Iij(t) when being t
The line current at quarter；F (X) is total network loss in the T periods；X is optimized variable and system state variables, and：
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In formula,For the charge power of electric automobile t, namely active power；There is provided for electric automobile
Reactive power regulated quantity；K is the numbering of the electric automobile in electric automobile cluster；
The bound for objective function of the active reactive optimal control includes operation of power networks constraints, grid power balances
Constraints and batteries of electric automobile energy storage constraint and charge power constraints；
Wherein, the operation of power networks constraints is：
Vmin≤|Vi(t)|≤Vmaxi∈N；
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In formula, Vi(t) for node i voltage amplitude, VmaxAnd VminThe respectively upper and lower limit of voltage deviation；Imax(t) it is circuit
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The grid power equilibrium constraint is：
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Voltage magnitude and phase angle；YijAnd θijThe respectively amplitude and phase angle of bus admittance matrix；
The batteries of electric automobile energy storage constraint and charge power constraints are respectively：
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In formula, CbatFor battery capacity, CeffFor the charge efficiency of electrically-charging equipment；It is the electronic vapour of kth at access node i
The initial cell energy storage state of car；SOCminAnd SOCmaxThe bound of battery energy storage during to be completed by charging electric vehicle；
SOCi,k(t) it is the battery electric quantity of kth electric automobile at access node i.
4. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 2), the object function of active power controller and its foundation side of constraints are carried out to electric automobile cluster
Method, comprise the following steps：
2.1) according to power network basic load, charging electric vehicle load and distributed power generation, have to electric automobile cluster
The object function of work(Reactive Power Control carries out equivalent-simplification, obtains carrying out electric automobile cluster the target of active optimization control
Function：
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<mi>T</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>L</mi>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>+</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>K</mi>
<mi>i</mi>
</msub>
</munderover>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>G</mi>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>;</mo>
</mrow>
In formula, F1(X) it is the net load quadratic sum comprising electric automobile and distributed power generation；Pi L(t)、Respectively access
The load and distributed power generation of node i；For the charging load of kth electric automobile；KiTo be electronic at access node i
Automobile quantity；
2.2) connecing according to the rated output power of charging electric vehicle facility, the charge power of different automobile types and grid requirements
Enter load range, obtain the active power regulation range constraint condition that the object function of active optimization control need to meet：
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>&le;</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mo>&lsqb;</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<msub>
<mi>f</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mrow>
</msub>
<mo>,</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>k</mi>
<mo>,</mo>
<msub>
<mi>v</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mrow>
</msub>
<mo>&rsqb;</mo>
<mo>;</mo>
</mrow>
<mrow>
<msub>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>L</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>K</mi>
<mi>i</mi>
</msub>
</munderover>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>G</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>&le;</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
<mo>;</mo>
</mrow>
In formula,WithThe respectively rated output power of charging electric vehicle facility and the maximum of different automobile types setting fills
Electrical power；Pi,minAnd Pi,maxThe load range that respectively electric automobile cluster access point is set according to grid requirements.
5. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 4), the object function and its constraints that are controlled according to the active optimization of foundation, in electric automobile cluster
The method that the charge power of all vehicles optimizes scheduling, comprises the following steps：
4.1) object function that the active optimization of foundation controls is decomposed, obtains being used to always fill in the realization of dispatching of power netwoks aspect
The upper strata optimization object function of electric load regulation, and for tracking lower floor's tracking control of each charging electric vehicle power of regulation
The object function of system；
4.2) according to upper strata optimization object function and grid load curve, carry out upper strata and optimize to obtain the total of electric automobile cluster
Charge load target；
4.3) according to total charging load of the electric automobile cluster obtained in lower floor's tracing control object function and step 4.2)
Target, active power regulation is carried out to each electric automobile in electric automobile cluster using scattered optimization method, obtains electronic vapour
Each electric automobile meets the active power regulation result that upper strata is always charged under load target in charge period in car cluster.
6. the electric automobile cluster power regulating method based on two benches cross-over control as claimed in claim 5, is characterised by：
In the step 4.1), the upper strata optimization object function is：
<mrow>
<mi>M</mi>
<mi>i</mi>
<mi>n</mi>
<mi>i</mi>
<mi>m</mi>
<mi>i</mi>
<mi>z</mi>
<mi>e</mi>
<mi> </mi>
<mi>G</mi>
<mrow>
<mo>(</mo>
<mi>Y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mi>L</mi>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>+</mo>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>a</mi>
<mi>v</mi>
</mrow>
<mi>L</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>;</mo>
</mrow>
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>a</mi>
<mi>v</mi>
</mrow>
<mi>L</mi>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<mrow>
<mo>(</mo>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mi>L</mi>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>k</mi>
<mi>v</mi>
</msub>
</munderover>
<msubsup>
<mi>P</mi>
<mi>k</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mi>T</mi>
</mfrac>
<mo>;</mo>
</mrow>
In formula, G (Y) is minimum load fluctuation；Y is optimized variableThat is electric automobile cluster always charges the target of load
Value；For meter and the load average value of charging electric vehicle；For the charge power of kth electric automobile；Born for power network
Lotus, and：
<mrow>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mi>L</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>L</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mi>i</mi>
<mi>G</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
The object function of lower floor's tracing control is：
<mrow>
<mi>M</mi>
<mi>i</mi>
<mi>n</mi>
<mi>i</mi>
<mi>m</mi>
<mi>i</mi>
<mi>z</mi>
<mi>e</mi>
<mi> </mi>
<mi>H</mi>
<mrow>
<mo>(</mo>
<mi>Z</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>K</mi>
<mi>i</mi>
</msub>
</munderover>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>;</mo>
</mrow>
In formula, H (Z) is the desired value of total charging loadWith the actual charge power of electric automobileBetween difference；
Z is optimized variable
7. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 5
In：In the step 4.3), according to total charging load target of lower floor's tracing control object function and electric automobile cluster, adopt
The method for carrying out active power regulation to electric automobile cluster with scattered optimization method, comprises the following steps：
4.3.1) total charging load target of electric automobile cluster is evenly distributed to the charge period of each electric automobile setting, and
According to the bound constraints of active power, the initial value of each charging electric vehicle power curve is calculated：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mo>&lsqb;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mn>...</mn>
<mo>,</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mi>T</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>;</mo>
</mrow>
4.3.2) according to the initial value of each charging electric vehicle power curve, each electric automobile in current electric automobile cluster is calculated
Difference between charge power summation and total charging load desired value：
<mrow>
<msubsup>
<mi>U</mi>
<mi>k</mi>
<mrow>
<mi>m</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
<mo>,</mo>
<mi>i</mi>
<mo>&NotEqual;</mo>
<mi>k</mi>
</mrow>
<mi>K</mi>
</munderover>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>m</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mi>n</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
In formula, m represents iterations；The charge power of the kth electric automobile obtained for last iteration；Kv=Ki×N
For electric automobile sum；
4.3.3) according to step 4.3.2) in obtained difference, to the charge power curve of each electric automobile in electric automobile cluster
Optimize, and its charge power curve is updated respectively according to the charge power optimized variable of each electric automobile；
The object function optimized to the charge power of each electric automobile in electric automobile cluster is：
<mrow>
<mi>M</mi>
<mi>i</mi>
<mi>n</mi>
<mi>i</mi>
<mi>m</mi>
<mi>i</mi>
<mi>z</mi>
<mi>e</mi>
<mi> </mi>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mi>Z</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>t</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<msup>
<mrow>
<mo>&lsqb;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msubsup>
<mi>U</mi>
<mi>k</mi>
<mrow>
<mi>m</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>;</mo>
</mrow>
In formula,The kth charging electric vehicle power optimization variable tried to achieve for current iteration, andFor
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mo>&lsqb;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>,</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
<mo>,</mo>
<mn>...</mn>
<mo>,</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>E</mi>
<mi>V</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mi>m</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mi>T</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>;</mo>
</mrow>
4.3.4 the difference in electric automobile cluster between each charge power summation and total charging load desired value after updating) is judged
Whether the condition of convergence is met, i.e. whether difference is less than the boundary value of setting or reaches the maximum iteration of setting：If not satisfied,
Then return to step 4.3.2), carry out next iteration；If satisfied, then iteration terminates, output result.
8. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 5), the object function of the grid-connected idle work optimization of electric automobile cluster and the foundation side of Reactive-power control constraints
Method, comprise the following steps：
5.1) born according to the charging electric vehicle facility Reactive-power control amount in idle work optimization period TQ and access charging electric vehicle
The operation of power networks state variable of lotus, establish the object function of the grid-connected idle work optimization of electric automobile；
5.2) according to each electric automobile in the electric automobile cluster obtained in charging electric vehicle facility operation characteristic and step 4)
Charging plan, establish the Reactive-power control constraints that the object function of idle work optimization need to meet；
5.3) idle work optimization is carried out to electric automobile cluster according to the object function of foundation and constraints, obtains electric automobile collection
The reactive power regulation result of each electric automobile in group.
9. the electric automobile cluster power regulating method based on two benches cross-over control, its feature exist as claimed in claim 1
In：In the step 5), the object function of the idle work optimization of foundation is：
<mrow>
<mi>M</mi>
<mi>i</mi>
<mi>n</mi>
<mi>i</mi>
<mi>m</mi>
<mi>i</mi>
<mi>z</mi>
<mi>e</mi>
<mi> </mi>
<msub>
<mi>F</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>X</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msub>
<mi>R</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>I</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>,</mo>
<mo>&ForAll;</mo>
<mi>t</mi>
<mo>&Element;</mo>
<mi>T</mi>
<mo>;</mo>
</mrow>
In formula, F2(X) it is total network loss of t, optimized variable X is the reactive power Q that electric automobile providesi,Ek V(t)；
The constraints of the idle work optimization is：
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>i</mi>
<mo>.</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>&le;</mo>
<msubsup>
<mi>S</mi>
<mrow>
<mi>f</mi>
<mi>R</mi>
</mrow>
<mn>2</mn>
</msubsup>
<mo>;</mo>
</mrow>
<mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>/</mo>
<mrow>
<mo>(</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>i</mi>
<mo>.</mo>
<mi>k</mi>
</mrow>
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<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<msup>
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<mo>(</mo>
<mi>t</mi>
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</mrow>
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</msup>
<mo>)</mo>
</mrow>
<mo>&GreaterEqual;</mo>
<mi>c</mi>
<mi>o</mi>
<mi>s</mi>
<mi>&theta;</mi>
</mrow>
In formula,For the rated capacity of charging electric vehicle facility；Cos θ represent minimum power factor during charging equipment work；The t active power optimal solution provided for first stage control, and
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>k</mi>
</mrow>
<mrow>
<mi>E</mi>
<mi>V</mi>
</mrow>
</msubsup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>&le;</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>V</mi>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
<mo>;</mo>
</mrow>
In formula, PvmaxFor the active power maximum of electric automobile.
10. a kind of be applied to such as the electric automobile collection based on two benches cross-over control of any one of claim 1~9 methods described
Group's power regulating system, it is characterised in that：It includes：
Grid-connected model construction module, for building the mixing of electric automobile cluster active reactive controls and pessimistic concurrency control, and according to institute
State and pessimistic concurrency control obtains the object function and its constraints to the progress active reactive optimal control of electric automobile cluster；
Active optimization object function builds module, for carrying out the target letter of active reactive optimal control based on electric automobile cluster
Number, the object function and its constraints that active optimization is carried out to electric automobile cluster is calculated；
Charge period division module, include active power regulation for the charge period of electric automobile cluster to be divided into several
Period and reactive power regulation period two adjust the charging electric vehicle power optimization period of period；
Active power optimization module, it is active excellent according to being carried out to electric automobile cluster within each active power regulation period
The object function and its constraints of change, active power regulation is carried out to electric automobile cluster；
Idle work optimization object function build module, for establish to electric automobile cluster carry out idle work optimization object function and its
Constraints；
Wattles power economic equivalent module, it is idle excellent according to being carried out to electric automobile cluster for being adjusted in each reactive power in the period
The object function and its constraints of change, reactive power regulation is carried out to electric automobile cluster.
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| CN113157801A (en) * | 2021-04-21 | 2021-07-23 | 内蒙古电力（集团）有限责任公司乌兰察布电业局 | Power utilization time sequence data visual display method and system and readable medium |
| CN113157801B (en) * | 2021-04-21 | 2023-07-11 | 内蒙古电力(集团)有限责任公司乌兰察布供电分公司 | Power utilization time sequence data visual display method, system and readable medium |
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