CN108462195A - A kind of the virtual energy storage capacity allocation method and system of electric vehicle - Google Patents
A kind of the virtual energy storage capacity allocation method and system of electric vehicle Download PDFInfo
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- CN108462195A CN108462195A CN201810169752.9A CN201810169752A CN108462195A CN 108462195 A CN108462195 A CN 108462195A CN 201810169752 A CN201810169752 A CN 201810169752A CN 108462195 A CN108462195 A CN 108462195A
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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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
- B60L53/64—Optimising energy costs, e.g. responding to electricity rates
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L55/00—Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Abstract
A kind of the virtual energy storage capacity allocation method and system of electric vehicle, including：Determine the virtual energy storage range of capacity of each electric vehicle charge-discharge region in wide area power distribution network；According to the virtual energy storage range of capacity of each electric vehicle charge-discharge region, the virtual energy storage capacity allocation plan of each electric vehicle when the grid-connected electric vehicle virtual energy storage total capacity maximum of wide area power distribution network is determined；Electric vehicle charge-discharge region is that the electric vehicle of same period distribution in wide area power distribution network is carried out subregion polymerization and is divided, each region corresponds to a node, specific distribution method is proposed according to the influence factor of each node, the safe operation for the grid-connected rear power grid of electric vehicle provides reliable reference.
Description
Technical field
The present invention relates to technical field of energy storage, and in particular to a kind of virtual energy storage capacity allocation method of electric vehicle and is
System.
Background technology
According to SAEC Society of Automotive Engineers of China《Energy saving and new energy technology route map》Newest prediction, in the year two thousand thirty new energy
Automobile volume of production and marketing is up to automobile total sales volume 40%, i.e., about 15,000,000 or so, the year two thousand twenty about 2,000,000 or so.With battery
The continuous of performance promotes and transports the steady forward of electrified process, and consumer can more receive new-energy automobile.V2G
The concept of (Vehicle to Grid) is well known, and refers to using electric vehicle as distributed energy storage unit, with charge and discharge
Form participates in the regulation and control of power grid.And the virtual energy storage system based on electric vehicle is to polymerize the electric vehicle subregion of wide area,
It is the distillation and in-depth of V2G concepts to realize the interaction of diversified forms between " vehicle " and " net ".
Investigation statistics shows that many private savings electric vehicles have 96% time to be in suspended state in one day, is available
Virtual energy storage capacity provides sufficient backup Redundancy, and the application for electric vehicle virtual energy storage provides feasibility.By wide area
The electric vehicle of dispersed placement carries out region clustering in distribution, and is carried out the electric vehicle of stagnation of movement as energy-storage units reasonably
Management control is allowed to realize the two-way exchange with power grid energy and information, to constitute electric vehicle virtual energy storage system.
Electric vehicle subregion is polymerize, while grid-connected work, to ensure the available stored energy capacitance of certain scale, with more
Mend that its single-point access capacity is small, the deficiency of place dispersion.And at the same time, virtual energy storage charges again may simultaneously in the distribution of region
Cause load to increase sharply, causes distribution network voltage landing violent, the network elements such as circuit, transformer overload serious problem, both shadow
The security reliability of user power utilization is rung, and needs to upgrade enlarging power distribution network, reduces economy.Ensureing power distribution network safety and stability fortune
Row, and under conditions of meeting background load power demand, how to determine the electric vehicle that power distribution network maximum can receive simultaneously
Grid connection capacity becomes urgently open question.Background load assigns all in addition to electric vehicle charge/discharge load in power grid
Load.
Although there is the professional standard limit value for different voltages grade energy storage maximum access capacity at present, do not consider
Actual load demand.The dump power that the difference for the general power and basic load for proposing to provide distribution is only limitted in relation to research is whole
Charging is provided for electric vehicle, does not consider power grid security nargin and the voltage change of individual node, and does not propose specifically to divide
Method of completing the square cannot provide reliable reference for the safe operation of the grid-connected rear power grid of electric vehicle.
Invention content
In order to solve the above-mentioned deficiency in the presence of the prior art, the present invention provides a kind of virtual energy storages of electric vehicle
Capacity allocation method and system.
Technical solution provided by the invention is：A kind of virtual energy storage capacity allocation method of electric vehicle, including：
Determine the virtual energy storage range of capacity of each electric vehicle charge-discharge region in wide area power distribution network；
According to the virtual energy storage range of capacity of each electric vehicle charge-discharge region, the grid-connected electronic vapour of wide area power distribution network is determined
The virtual energy storage capacity allocation plan of each electric vehicle when vehicle virtual energy storage total capacity maximum；
The electric vehicle charge-discharge region is that the electric vehicle of same period distribution in wide area power distribution network is carried out subregion
Domain polymerize and divides, and each region corresponds to a node.
Preferably, in the determining wide area power distribution network each electric vehicle charge-discharge region virtual energy storage range of capacity, packet
It includes：
According to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determine have electric vehicle it is grid-connected when operation ginseng
Number；
According to it is described have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraints, determine each node
Virtual energy storage range of capacity.
Preferably, the operating parameter includes：The load factor of the voltage of node, the load factor of transformer and circuit.
Preferably, operating parameter when grid-connected without electric vehicle in the power distribution network according to wide area, determination have electric vehicle simultaneously
Operating parameter when net, including：
Determined by following formula have electric vehicle it is grid-connected when each node voltage：
Determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
Determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages dock
Enter the susceptibility of the electric automobile load of the point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node
The virtual energy storage capacity of i；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；LT：The load of transformer
Rate；LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：The number of transformer, M1For positive integer；αi：Transformer
To accessing the susceptibility of i point electric automobile loads；LC：The load factor of circuit；LC0：Original negative without electric vehicle circuit when grid-connected
Load rate；M2：The item number of circuit, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
Preferably, the preset operating parameter constraints, including：
The voltage constraints of node, such as following formula：
Vmin≤Vi≤Vmax
The load factor constraints of transformer, such as following formula：
LT≤LTlimit
The load factor constraints of circuit, such as following formula：
LC≤LClimit
In formula：Vmin：The minimum value of node voltage；Vmax：The maximum value of node voltage；LTlimit：Transformer load rate is faced
Dividing value；LClimit：The critical value of line load rate.
Preferably, the basis have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraints, determine
The virtual energy storage range of capacity of each node, including：
Respectively according to have electric vehicle it is grid-connected when the voltage of each node, each transformer load factor, the load factor of each circuit
And the load factor constraints of corresponding node voltage constraints, the load factor constraints of transformer and circuit, it determines
First, second, third virtual energy storage range of capacity；
According to the first, second, third virtual energy storage range of capacity, the virtual energy storage range of capacity of each node is determined.
Preferably, according to the first, second, third virtual energy storage range of capacity, the virtual energy storage capacity model of each node is determined
It encloses, including：
According to the intersection of the first, second, third virtual energy storage range of capacity, determine that the virtual energy storage of each node holds
Measure range.
Preferably, the virtual energy storage range of capacity according to each electric vehicle charge-discharge region, determines wide area power distribution network
The virtual energy storage capacity allocation plan of each electric vehicle when grid-connected electric vehicle virtual energy storage total capacity maximum, including：
According to the virtual energy storage range of capacity of each node and the object function built in advance, determined by linear programming algorithm
The virtual energy storage capacity allocation plan of electric vehicle in each node；
The object function built in advance is built according to the virtual energy storage capacity of each node.
Preferably, each electric vehicle when the grid-connected electric vehicle virtual energy storage total capacity maximum of the determining wide area power distribution network
Virtual energy storage capacity allocation plan after, further include：
The virtual energy storage capacity allocation plan of each electric vehicle when to virtual energy storage total capacity maximum carries out Power flow simulation
It calculates；
When the load factor of the voltage of each node, the load factor of transformer and circuit is satisfied by the preset operating parameter about
Beam condition, then the virtual energy storage capacity allocation plan of the electric vehicle is available；Otherwise the virtual energy storage capacity of the electric vehicle point
It is unavailable with scheme.
Preferably, available electric vehicle capacity allocation plan is exported to being uploaded to control centre.
Preferably, the object function is shown below：
In formula：PEVmax：The virtual energy storage total capacity of wide area network；N：The areal divided in wide area network, N are positive integers；
PEVi：The virtual energy storage capacity of node i.
Based on same inventive concept, the present invention also provides a kind of virtual energy storage capacity distribution system of electric vehicle, packets
It includes：
Determining module, the virtual energy storage range of capacity for determining each electric vehicle charge-discharge region in wide area power distribution network；
Distribution module determines wide area distribution for the virtual energy storage range of capacity according to each electric vehicle charge-discharge region
Net the virtual energy storage capacity allocation plan of each electric vehicle when grid-connected electric vehicle virtual energy storage total capacity maximum；
Division module, for the electric vehicle charge-discharge region be by wide area power distribution network the distribution of same period it is electronic
Automobile carries out subregion polymerization and divides, and each region corresponds to a node.
Preferably, the distribution module, including：
First determination unit, for according to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determine have it is electronic
Operating parameter when automobile is grid-connected；
Second determination unit, for according to described in have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraint
Condition determines the virtual energy storage range of capacity of each node.
Preferably, the distribution module further includes：
First computing unit, for determined by following formula have electric vehicle it is grid-connected when each node voltage：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages dock
Enter the susceptibility of the electric automobile load of the point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node
The virtual energy storage capacity of i；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；
Second computing unit, for determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
In formula：LT：The load factor of transformer；LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：Transformation
The number of device, M1For positive integer；αi：Susceptibility of the transformer to access i point electric automobile loads；
Third computing unit, for determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula：LC：The load factor of circuit；LC0：Initial load rate without electric vehicle circuit when grid-connected；M2：The item of circuit
Number, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
Compared with the immediate prior art, technical solution provided by the invention has the advantages that：
Technical solution provided by the invention determines that the virtual energy storage of each electric vehicle charge-discharge region in wide area power distribution network holds
Amount range determines the grid-connected electronic vapour of wide area power distribution network according to the virtual energy storage range of capacity of each electric vehicle charge-discharge region
The virtual energy storage capacity allocation plan of each electric vehicle when vehicle virtual energy storage total capacity maximum, wherein electric vehicle charge and discharge area
Domain is that the electric vehicle of same period distribution in wide area power distribution network is carried out subregion polymerization and is divided, and each region corresponds to one
A node proposes specific distribution method according to the influence factor of each node, is the safety fortune of power grid after electric vehicle is grid-connected
Row provides reliable reference.
Technical solution provided by the invention realizes and improves the access capability of regional distribution network renewable energy power generation, cuts
Peak load participates in ancillary service and improves the effect of power quality.
Technical solution provided by the invention, it is contemplated that same period, each access point additional electric driving vapour of wide area distribution
The influence of the assembly effect and all node voltages, network element load factor of vehicle charging load, using first order network sensitivity
Analytic approach, the voltage of power distribution network safe operation, load factor limit value with reference to as defined in the relevant technologies, to realize the period wide area distribution
It nets grid-connected electric vehicle virtual energy storage total capacity and is up to target, the computational methods may be used and determine that wide area distribution maximum permits
Perhaps grid-connected electric vehicle virtual energy storage total capacity.
Technical solution provided by the invention calculates the optimal combination point of each subregion grid node electric vehicle by optimizing
With capacity, scheduling decision person is helped to provide reference scheme, had not only made full use of existing power distribution network capacity, but also ensure no more than power grid
Safe operating conditions reduce power grid expansion investments cost.
Description of the drawings
Fig. 1 is a kind of flow chart of the virtual energy storage capacity allocation method of electric vehicle in the present invention；
Fig. 2 is the structure chart of virtual energy storage capacity allocation method in the embodiment of the present invention；
Fig. 3 is the virtual energy storage system diagram based on electric vehicle in the embodiment of the present invention.
Specific implementation mode
For a better understanding of the present invention, present disclosure is done further with example with reference to the accompanying drawings of the specification
Explanation.
Fig. 1 is a kind of flow chart of the virtual energy storage capacity allocation method of electric vehicle in the present invention, as shown in Figure 1, packet
It includes：
Step S101 determines the virtual energy storage range of capacity of each electric vehicle charge-discharge region in wide area power distribution network；
Step S102 determines wide area power distribution network simultaneously according to the virtual energy storage range of capacity of each electric vehicle charge-discharge region
The virtual energy storage capacity allocation plan of each electric vehicle when the electric vehicle virtual energy storage total capacity maximum of net；
Step S103, the electric vehicle charge-discharge region are by the electric vehicle of same period distribution in wide area power distribution network
It carries out subregion polymerization and divides, each region corresponds to a node.
Specifically, step S102 determines that wide area is matched according to the virtual energy storage range of capacity of each electric vehicle charge-discharge region
The virtual energy storage capacity allocation plan of each electric vehicle when the grid-connected electric vehicle virtual energy storage total capacity maximum of power grid, including：
According to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determine have electric vehicle it is grid-connected when operation ginseng
Number；
According to it is described have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraints, determine each node
Virtual energy storage range of capacity.
Wherein operating parameter includes：The load factor of the voltage of node, the load factor of transformer and circuit；And maximum charge and discharge
Electric current, voltage fluctuation and flicker, Voltage unbalance, capacity of short circuit.
Further, according to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determination have electric vehicle grid-connected
When operating parameter, including：
Determined by following formula have electric vehicle it is grid-connected when each node voltage：
Determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
Determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages dock
Enter the susceptibility of the electric automobile load of the point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node
The virtual energy storage capacity of i；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；LT：The load of transformer
Rate；LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：The number of transformer, M1For positive integer；αi：Transformer
To accessing the susceptibility of i point electric automobile loads；LC：The load factor of circuit；LC0：Original negative without electric vehicle circuit when grid-connected
Load rate；M2：The item number of circuit, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
In embodiment, preset operating parameter constraints, including：
The voltage constraints of node, such as following formula：
Vmin≤Vi≤Vmax
The load factor constraints of transformer, such as following formula：
LT≤LTlimit
The load factor constraints of circuit, such as following formula：
LC≤LClimit
In formula：Vmin：The minimum value of node voltage；Vmax：The maximum value of node voltage；LTlimit：Transformer load rate is faced
Dividing value；LClimit：The critical value of line load rate.
In embodiment, according to have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraints, determine every
The virtual energy storage range of capacity of a node, including：
Respectively according to have electric vehicle it is grid-connected when the voltage of each node, each transformer load factor, the load factor of each circuit
And the load factor constraints of corresponding node voltage constraints, the load factor constraints of transformer and circuit, it determines
First, second, third virtual energy storage range of capacity；
According to the intersection of the first, second, third virtual energy storage range of capacity, the virtual energy storage capacity model of each node is determined
It encloses.
In embodiment, according to the virtual energy storage range of capacity of each electric vehicle charge-discharge region, wide area power distribution network is determined simultaneously
The virtual energy storage capacity allocation plan of each electric vehicle when the electric vehicle virtual energy storage total capacity maximum of net, including：
According to the virtual energy storage range of capacity of each node and the object function built in advance, determined by linear programming algorithm
The virtual energy storage capacity allocation plan of electric vehicle in each node；
The object function built in advance is built according to the sum of the virtual energy storage maximum size of each node.
Wherein, object function is shown below：
In formula：PEVmax：The virtual energy storage total capacity of wide area network；N：The areal divided in wide area network, N are positive integers；
PEVi：The virtual energy storage capacity of node i.
Further, each electric vehicle when the grid-connected electric vehicle virtual energy storage total capacity maximum of wide area power distribution network is determined
After virtual energy storage capacity allocation plan, further include：
The virtual energy storage capacity allocation plan of each electric vehicle when to virtual energy storage total capacity maximum carries out Power flow simulation
It calculates；
Item is constrained when the load factor of the voltage of each node, the load factor of transformer and circuit is satisfied by preset operating parameter
Part, then the virtual energy storage capacity allocation plan of the electric vehicle is available；Otherwise the virtual energy storage capacity distribution side of the electric vehicle
Case is unavailable.
Available electric vehicle capacity allocation plan is exported to being uploaded to control centre.
Fig. 2, be the embodiment of the present invention in virtual energy storage capacity allocation method structure chart, as shown in Fig. 2, specifically include with
Lower step：
1) it is illustrated in figure 3 the virtual energy storage system diagram based on electric vehicle, the electronic vapour that will be distributed in wide area power distribution network
Vehicle carries out subregion polymerization, is divided into multiple electric vehicle charge-discharge region (EVDomain i), a region corresponds to a node；Each
Region includes m electric vehicle charge and discharge station (EVField j), each station can provide service (EV for n electric vehicleVehicle k)。
2) real-time update background load data records the load factor of the voltage of each node, network element in wide area distribution.
3) trend sensitivity Simulation Analysis is carried out, the specific method is as follows：
When (3-1) considers a certain node additional electric driving car load in wide area distribution, to all node voltages and therewith phase
The network element load factor of pass has an impact, using network one order, a certain moment access point i of approximate calculation as the following formula
Voltage：
The load factor of transformer is calculated as follows：
The load factor of circuit is calculated as follows：
In formula, Vi：The voltage of node i；Vi0It is the initial voltage of node i when no electric vehicle is grid-connected, μi：I point voltages pair
Access the susceptibility of the electric automobile load of the point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Section
The virtual energy storage capacity of point i；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；LT：Transformer is born
Load rate；LT0：Initial load rate without electric vehicle transformer when grid-connected；LC0：Initial load without electric vehicle circuit when grid-connected
Rate；M1：The number of transformer, M1For positive integer；αi：Susceptibility of the transformer to access i point electric automobile loads；LC：Circuit
Load factor；M2：The number of circuit, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
(3-2) carries out trend sensitivity analysis using the data that step 2) records：Calculate separately period voltage sensitivity
Factor μ, the sensitivity factors β of the sensitivity factors α of the load factor of transformer and the load factor of circuit.
4) according to correlation standard, to ensure that power distribution network safe and stable operation condition is constraint：
Vmin≤Vi≤Vmax
LT≤LTlimit
LC≤LClimit
To realize that the grid-connected electric vehicle virtual energy storage total capacity of the period wide area power distribution network is up to object function, establish
Linear equation is shown below；
In formula：Vi：The voltage of node i；LT：The load factor of transformer；LC：The load factor of circuit；LTlimit：Transformer load
The critical value of rate；LClimit：The critical value of line load rate；PEVmax：The virtual energy storage total capacity of wide area network；N：It is drawn in wide area network
The areal divided, N is positive integer.
5) linear programming algorithm is utilized, the optimal combination partition capacity of each subregion grid node electric vehicle is calculated, from
And determine target function value；
6) data of step 2) and step 5) are subjected to result verification：
(6-1) carries out Load flow calculation, and the voltage for judging to calculate according to limits value as defined in step 4) using above-mentioned data
Or whether safety is not out-of-limit for load factor；
(6-2) is neither out-of-limit, and obtained prioritization scheme is available, and available electric vehicle capacity allocation plan is exported
To being uploaded to control centre；Otherwise, prioritization scheme is unavailable, return to step 2) it recalculates.
7) calculating process terminates.
Based on same design, the present invention also provides a kind of virtual energy storage capacity distribution systems of electric vehicle, including：
Determining module, the virtual energy storage range of capacity for determining each electric vehicle charge-discharge region in wide area power distribution network；
Distribution module determines wide area distribution for the virtual energy storage range of capacity according to each electric vehicle charge-discharge region
Net the virtual energy storage capacity allocation plan of each electric vehicle when grid-connected electric vehicle virtual energy storage total capacity maximum；
Division module, for the electric vehicle charge-discharge region be by wide area power distribution network the distribution of same period it is electronic
Automobile carries out subregion polymerization and divides, and each region corresponds to a node.
Preferably, the distribution module, including：
First determination unit, for according to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determine have it is electronic
Operating parameter when automobile is grid-connected；
Second determination unit, for according to described in have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraint
Condition determines the virtual energy storage range of capacity of each node.
Preferably, the distribution module further includes：
First computing unit, for determined by following formula have electric vehicle it is grid-connected when each node voltage：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages dock
Enter the susceptibility of the electric automobile load of the point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node
The virtual energy storage capacity of i；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；
Second computing unit, for determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
In formula：LT：The load factor of transformer；LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：Transformation
The number of device, M1For positive integer；αi：Susceptibility of the transformer to access i point electric automobile loads；
Third computing unit, for determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula：LC：The load factor of circuit；LC0：Initial load rate without electric vehicle circuit when grid-connected；M2：The item of circuit
Number, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, the application can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The application is with reference to method, the flow of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
It these are only the embodiment of the present invention, be not intended to restrict the invention, it is all in the spirit and principles in the present invention
Within, any modification, equivalent substitution, improvement and etc. done, be all contained in apply pending scope of the presently claimed invention it
It is interior.
Claims (14)
1. a kind of virtual energy storage capacity allocation method of electric vehicle, which is characterized in that including：
Determine the virtual energy storage range of capacity of each electric vehicle charge-discharge region in wide area power distribution network；
According to the virtual energy storage range of capacity of each electric vehicle charge-discharge region, determine that the grid-connected electric vehicle of wide area power distribution network is empty
The virtual energy storage capacity allocation plan of each electric vehicle when quasi- energy storage total capacity maximum；
The electric vehicle charge-discharge region is that the electric vehicle of same period distribution in wide area power distribution network is carried out subregion to gather
It closes and divides, each region corresponds to a node.
2. virtual energy storage capacity allocation method as described in claim 1, which is characterized in that each in the determining wide area power distribution network
The virtual energy storage range of capacity of electric vehicle charge-discharge region, including：
According to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determine have electric vehicle it is grid-connected when operating parameter；
According to it is described have electric vehicle it is grid-connected when operating parameter and preset operating parameter constraints, determine the virtual of each node
Stored energy capacitance range.
3. virtual energy storage capacity allocation method as claimed in claim 2, which is characterized in that the operating parameter includes：Node
Voltage, the load factor of transformer and the load factor of circuit.
4. virtual energy storage capacity allocation method as claimed in claim 3, which is characterized in that nothing in the power distribution network according to wide area
Operating parameter when electric vehicle is grid-connected, determine have electric vehicle it is grid-connected when operating parameter, including：
Determined by following formula have electric vehicle it is grid-connected when each node voltage：
Determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
Determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages should to access
The susceptibility of the electric automobile load of point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node i
Virtual energy storage capacity；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；LT：The load factor of transformer；
LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：The number of transformer, M1For positive integer；αi：Transformer docks
Enter the susceptibility of i point electric automobile loads；LC：The load factor of circuit；LC0：Initial load without electric vehicle circuit when grid-connected
Rate；M2：The item number of circuit, M2For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
5. virtual energy storage capacity allocation method as claimed in claim 4, which is characterized in that the preset operating parameter constraint
Condition, including：
The voltage constraints of node, such as following formula：
Vmin≤Vi≤Vmax
The load factor constraints of transformer, such as following formula：
LT≤LTlimit
The load factor constraints of circuit, such as following formula：
LC≤LClimit
In formula：Vmin：The minimum value of node voltage；Vmax：The maximum value of node voltage；LTlimit：Transformer load rate it is critical
Value；LClimit：The critical value of line load rate.
6. virtual energy storage capacity allocation method as claimed in claim 5, which is characterized in that the basis has electric vehicle grid-connected
When operating parameter and preset operating parameter constraints, determine the virtual energy storage range of capacity of each node, including：
Respectively according to have electric vehicle it is grid-connected when the voltage of each node, the load factor of each transformer, the load factor of each circuit and
The load factor constraints of corresponding node voltage constraints, the load factor constraints of transformer and circuit, determine first,
Second, third virtual energy storage range of capacity；
According to the first, second, third virtual energy storage range of capacity, the virtual energy storage range of capacity of each node is determined.
7. virtual energy storage capacity allocation method as claimed in claim 6, which is characterized in that virtual according to first, second, third
Stored energy capacitance range determines the virtual energy storage range of capacity of each node, including：
According to the intersection of the first, second, third virtual energy storage range of capacity, the virtual energy storage capacity model of each node is determined
It encloses.
8. virtual energy storage capacity allocation method as described in claim 1, which is characterized in that described according to each electric vehicle charge and discharge
The virtual energy storage range of capacity in electric region determines each electricity when the grid-connected electric vehicle virtual energy storage total capacity maximum of wide area power distribution network
The virtual energy storage capacity allocation plan of electrical automobile, including：
According to the virtual energy storage range of capacity of each node and the object function built in advance, each section is determined by linear programming algorithm
The virtual energy storage capacity allocation plan of electric vehicle in point；
The object function built in advance is built according to the virtual energy storage capacity of each node.
9. virtual energy storage capacity allocation method as described in claim 1, which is characterized in that the determining wide area power distribution network is grid-connected
Electric vehicle virtual energy storage total capacity maximum when each electric vehicle virtual energy storage capacity allocation plan after, further include：
The virtual energy storage capacity allocation plan of each electric vehicle when to virtual energy storage total capacity maximum carries out Power flow simulation calculating；
Item is constrained when the load factor of the voltage of each node, the load factor of transformer and circuit is satisfied by the preset operating parameter
Part, then the virtual energy storage capacity allocation plan of the electric vehicle is available；Otherwise the virtual energy storage capacity distribution side of the electric vehicle
Case is unavailable.
10. virtual energy storage capacity allocation method as claimed in claim 9, which is characterized in that by available electric vehicle capacity
Allocation plan is exported to being uploaded to control centre.
11. virtual energy storage capacity allocation method as claimed in claim 8, which is characterized in that the object function such as following formula institute
Show：
In formula：PEVmax：The virtual energy storage total capacity of wide area network；N：The areal divided in wide area network, N are positive integers；PEVi：
The virtual energy storage capacity of node i.
12. a kind of virtual energy storage capacity distribution system of electric vehicle, which is characterized in that including：
Determining module, the virtual energy storage range of capacity for determining each electric vehicle charge-discharge region in wide area power distribution network；
Distribution module determines wide area power distribution network simultaneously for the virtual energy storage range of capacity according to each electric vehicle charge-discharge region
The virtual energy storage capacity allocation plan of each electric vehicle when the electric vehicle virtual energy storage total capacity maximum of net；
Division module is by the electric vehicle of same period distribution in wide area power distribution network for the electric vehicle charge-discharge region
It carries out subregion polymerization and divides, each region corresponds to a node.
13. virtual energy storage capacity distribution system as claimed in claim 12, which is characterized in that the distribution module, including：
First determination unit, for according to it is grid-connected without electric vehicle in wide area power distribution network when operating parameter, determination have electric vehicle
Operating parameter when grid-connected；
Second determination unit, for according to described in have electric vehicle it is grid-connected when operating parameter and preset operating parameter constrain item
Part determines the virtual energy storage range of capacity of each node.
14. virtual energy storage capacity distribution system as claimed in claim 12, which is characterized in that the distribution module further includes：
First computing unit, for determined by following formula have electric vehicle it is grid-connected when each node voltage：
In formula, Vi：The voltage of node i；Vi0：Initial voltage without electric vehicle node i when grid-connected；μi：I point voltages should to access
The susceptibility of the electric automobile load of point；μij：Susceptibility of the i point voltages to access j point electric automobile loads；PEVi：Node i
Virtual energy storage capacity；PEVj：The virtual energy storage capacity of node j；N：Node number, N are positive integers；
Second computing unit, for determined by following formula have electric vehicle it is grid-connected when each transformer load factor：
In formula：LT：The load factor of transformer；LT0：Initial load rate without electric vehicle transformer when grid-connected；M1：Of transformer
Number, M1For positive integer；αi：Susceptibility of the transformer to access i point electric automobile loads；
Third computing unit, for determined by following formula have electric vehicle it is grid-connected when each circuit load factor：
In formula：LC：The load factor of circuit；LC0：Initial load rate without electric vehicle circuit when grid-connected；M2：The item number of circuit, M2
For positive integer；βi：Susceptibility of the circuit to access i point electric automobile loads.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109412159A (en) * | 2018-12-07 | 2019-03-01 | 国网冀北电力有限公司经济技术研究院 | Transformer load rate controls device and method |
| US11757285B2 (en) | 2021-05-14 | 2023-09-12 | Huawei Digital Power Technologies Co., Ltd. | Energy storage system and related method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103840521A (en) * | 2014-02-27 | 2014-06-04 | 武汉大学 | Large-scale electric vehicle optimized charging and discharging system and method based on the optimal power flow |
| CN106058904A (en) * | 2016-06-30 | 2016-10-26 | 全球能源互联网研究院 | Capacity matching method for energy storage type electric vehicle charging pile |
-
2018
- 2018-02-28 CN CN201810169752.9A patent/CN108462195B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103840521A (en) * | 2014-02-27 | 2014-06-04 | 武汉大学 | Large-scale electric vehicle optimized charging and discharging system and method based on the optimal power flow |
| CN106058904A (en) * | 2016-06-30 | 2016-10-26 | 全球能源互联网研究院 | Capacity matching method for energy storage type electric vehicle charging pile |
Non-Patent Citations (3)
| Title |
|---|
| 李振坤等: "基于时序电压灵敏度的有源配电网储能优化配置", 《中国电机工程学报》 * |
| 王锡凡等: "电动汽车充电负荷与调度控制策略综述", 《中国电机工程学报》 * |
| 胡泽春等: "电动汽车接入电网的影响与利用", 《中国电机工程学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109412159A (en) * | 2018-12-07 | 2019-03-01 | 国网冀北电力有限公司经济技术研究院 | Transformer load rate controls device and method |
| US11757285B2 (en) | 2021-05-14 | 2023-09-12 | Huawei Digital Power Technologies Co., Ltd. | Energy storage system and related method |
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