CN108462195B - Virtual energy storage capacity distribution method and system for electric automobile - Google Patents

Virtual energy storage capacity distribution method and system for electric automobile Download PDF

Info

Publication number
CN108462195B
CN108462195B CN201810169752.9A CN201810169752A CN108462195B CN 108462195 B CN108462195 B CN 108462195B CN 201810169752 A CN201810169752 A CN 201810169752A CN 108462195 B CN108462195 B CN 108462195B
Authority
CN
China
Prior art keywords
energy storage
storage capacity
virtual energy
electric automobile
node
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810169752.9A
Other languages
Chinese (zh)
Other versions
CN108462195A (en
Inventor
刘超群
李蓓
全慧
李建林
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Electric Power Research Institute Co Ltd CEPRI
Original Assignee
China Electric Power Research Institute Co Ltd CEPRI
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Electric Power Research Institute Co Ltd CEPRI filed Critical China Electric Power Research Institute Co Ltd CEPRI
Priority to CN201810169752.9A priority Critical patent/CN108462195B/en
Publication of CN108462195A publication Critical patent/CN108462195A/en
Application granted granted Critical
Publication of CN108462195B publication Critical patent/CN108462195B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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 virtual energy storage capacity distribution method and system of an electric automobile comprise the following steps: determining a virtual energy storage capacity range of each electric vehicle charging and discharging area in a wide area power distribution network; determining a virtual energy storage capacity distribution scheme of each electric automobile when the total virtual energy storage capacity of the electric automobiles of the wide area power distribution network is the maximum according to the virtual energy storage capacity range of each electric automobile charging and discharging area; the charging and discharging areas of the electric automobile are divided by carrying out regional aggregation on the electric automobiles distributed in the same time period in a wide area power distribution network, each area corresponds to one node, a specific distribution method is provided according to influence factors of each node, and reliable reference is provided for safe operation of a power grid after the electric automobiles are connected to the power grid.

Description

Virtual energy storage capacity distribution method and system for electric automobile
Technical Field
The invention relates to the technical field of energy storage, in particular to a virtual energy storage capacity distribution method and system for an electric automobile.
Background
According to the latest prediction of the energy-saving and new energy technology roadmap of the China automobile engineering society, the new energy automobile output and sales volume reaches 40% of the total automobile sales volume in 2030 years, namely about 1500 thousands of automobiles, and about 200 thousands of automobiles in 2020. With the continuous improvement of the battery performance and the steady advance of the transportation electrification process, consumers can accept new energy automobiles more. The concept of V2G (Vehicle to Grid) is widely known, and refers to that an electric Vehicle is used as a distributed energy storage unit to participate in regulation and control of a power Grid in a charging and discharging manner. The virtual energy storage system based on the electric automobile aggregates the wide-area electric automobiles in different areas, so that various forms of interaction between the automobiles and the networks are realized, and the sublimation and deepening of the V2G concept are realized.
Research statistics show that many private electric vehicles stop running 96% of the time a day, sufficient backup redundancy is provided for available virtual energy storage capacity, and feasibility is provided for application of virtual energy storage of electric vehicles. The electric vehicles distributed in the wide area distribution network are subjected to regional aggregation, and the stopped electric vehicles are used as energy storage units to be reasonably managed and controlled, so that the bidirectional exchange of energy and information with a power grid is realized, and the virtual energy storage system of the electric vehicles is formed.
The electric automobiles are gathered in different areas and are simultaneously connected to the grid, so that the available energy storage capacity of a certain scale is ensured, and the defects of small single-point access capacity and scattered places of the electric automobiles are overcome. Meanwhile, virtual energy storage in the regional distribution network is charged simultaneously, and load surge can be caused, so that the problems of severe voltage drop of the distribution network and severe overload of network elements such as lines and transformers are caused, the safety and reliability of power utilization of users are influenced, the distribution network needs to be upgraded and expanded, and the economical efficiency is reduced. Under the conditions of ensuring the safe and stable operation of the power distribution network and meeting the background load power consumption requirement, how to determine the maximum electric vehicle grid-connected capacity which can be simultaneously accepted by the power distribution network becomes a problem to be researched urgently. Background loads assign all loads in the grid except for electric car charge/discharge loads.
At present, although there are industry standard limits for the maximum access capacity of energy storage for different voltage classes, the actual load requirements are not considered. The related research is limited to providing that all residual power of the difference between the total power and the basic load provided by the distribution network is used for charging the electric automobile, the safety margin of the power grid and the voltage change of a single node are not considered, and a specific distribution method is not provided, so that a reliable reference can not be provided for the safe operation of the power grid after the electric automobile is connected to the power grid.
Disclosure of Invention
In order to solve the above defects in the prior art, the invention provides a virtual energy storage capacity allocation method and system for an electric vehicle.
The technical scheme provided by the invention is as follows: a virtual energy storage capacity distribution method of an electric automobile comprises the following steps:
determining a virtual energy storage capacity range of each electric vehicle charging and discharging area in a wide area power distribution network;
determining a virtual energy storage capacity distribution scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide area power distribution network grid connection is maximum according to the virtual energy storage capacity range of each electric vehicle charge and discharge area;
the electric vehicle charging and discharging areas are divided by carrying out regional aggregation on electric vehicles distributed in the wide area power distribution network at the same time period, and each area corresponds to one node.
Preferably, the determining the virtual energy storage capacity range of each electric vehicle charging and discharging area in the wide area power distribution network includes:
determining the running parameters of the electric automobile when the electric automobile is connected to the grid according to the running parameters of the electric automobile when the electric automobile is not connected to the grid in the wide area power distribution network;
and determining the virtual energy storage capacity range of each node according to the operation parameters of the electric automobile during grid connection and preset operation parameter constraint conditions.
Preferably, the operating parameters include: the voltage at the node, the load factor of the transformer and the load factor of the line.
Preferably, the determining the operation parameters when the electric vehicle is connected to the grid according to the operation parameters when the electric vehicle is not connected to the grid in the wide area distribution network comprises:
the voltage of each node when the electric automobile is connected to the grid is determined according to the following formula:
Figure BDA0001585022910000021
determining the load rate of each transformer when the electric automobile is connected to the grid by the following formula:
Figure BDA0001585022910000022
determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000031
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : sensitivity of i-point voltage to electric vehicle load connected to the pointSensitivity; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p is EVi : virtual energy storage capacity of node i; p is EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer; l is a radical of an alcohol T : the load factor of the transformer; l is a radical of an alcohol T0 : the initial load rate of the transformer when the electric automobile is connected to the grid is avoided; m is a group of 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i; l is a radical of an alcohol C : the load factor of the line; l is a radical of an alcohol C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m 2 : number of lines, M 2 Is a positive integer; beta is a i : line sensitivity to access i-point electric vehicle loads.
Preferably, the preset operating parameter constraint condition includes:
the voltage constraint of the node is as follows:
V min ≤V i ≤V max
the load factor constraint of the transformer is as follows:
L T ≤L Tlimit
the load rate constraint of the line is as follows:
L C ≤L Climit
in the formula: v min : the minimum value of the node voltage; v max : the maximum value of the node voltage; l is a radical of an alcohol Tlimit : a critical value of the load factor of the transformer; l is Climit : line load rate threshold.
Preferably, the determining the virtual energy storage capacity range of each node according to the operation parameters when the electric vehicle is connected to the grid and the preset operation parameter constraint conditions includes:
determining a first virtual energy storage capacity range, a second virtual energy storage capacity range and a third virtual energy storage capacity range according to the voltage of each node, the load rate of each transformer, the load rate of each line and the corresponding node voltage constraint condition, the load rate constraint condition of the transformer and the load rate constraint condition of the line when the electric automobile is connected to the grid;
and determining the virtual energy storage capacity range of each node according to the first, second and third virtual energy storage capacity ranges.
Preferably, determining the virtual energy storage capacity range of each node according to the first, second, and third virtual energy storage capacity ranges includes:
and determining the virtual energy storage capacity range of each node according to the intersection of the first, second and third virtual energy storage capacity ranges.
Preferably, the determining, according to the virtual energy storage capacity range of each electric vehicle charge-discharge region, the virtual energy storage capacity allocation scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicle of the wide area power distribution network grid connection is the maximum includes:
determining a virtual energy storage capacity allocation scheme of the electric automobile in each node through a linear programming algorithm according to the virtual energy storage capacity range of each node and a pre-constructed objective function;
and the pre-constructed objective function is constructed according to the virtual energy storage capacity of each node.
Preferably, after determining the virtual energy storage capacity allocation scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide area power distribution network grid-connected is maximum, the method further includes:
carrying out load flow simulation calculation on the virtual energy storage capacity distribution scheme of each electric automobile when the total virtual energy storage capacity is maximum;
when the voltage of each node, the load rate of the transformer and the load rate of the line all meet the preset operation parameter constraint condition, the virtual energy storage capacity allocation scheme of the electric automobile is available; otherwise, the virtual energy storage capacity allocation scheme of the electric automobile is unavailable.
Preferably, the available electric vehicle capacity allocation schemes are output to the dispatching center.
Preferably, the objective function is represented by the following formula:
Figure BDA0001585022910000041
in the formula: p EVmax : virtual total energy storage capacity of the wide area network; n: the number of divided areas in the wide area network, wherein N is a positive integer; p is EVi : virtual energy storage capacity of node i.
Based on the same inventive concept, the invention also provides a virtual energy storage capacity distribution system of the electric automobile, which comprises:
the determining module is used for determining the virtual energy storage capacity range of each electric automobile charging and discharging area in the wide area power distribution network;
the distribution module is used for determining a virtual energy storage capacity distribution scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide-area power distribution network grid-connected is maximum according to the virtual energy storage capacity range of each electric vehicle charge-discharge area;
and the division module is used for dividing the electric automobile charging and discharging areas distributed in the same time period in the wide area power distribution network by carrying out regional aggregation, and each area corresponds to one node.
Preferably, the distribution module includes:
the first determining unit is used for determining the running parameters of the electric automobile when the electric automobile is connected in the grid according to the running parameters of the electric automobile when the electric automobile is not connected in the wide area power distribution network;
and the second determining unit is used for determining the virtual energy storage capacity range of each node according to the running parameters when the electric automobile is connected to the grid and the preset running parameter constraint conditions.
Preferably, the distribution module further includes:
the first calculation unit is used for determining the voltage of each node when the electric automobile is connected to the grid according to the following formula:
Figure BDA0001585022910000051
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p EVi : virtual energy storage capacity of node i; p EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer;
the second calculating unit is used for determining the load rate of each transformer when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000052
in the formula: l is T : the load factor of the transformer; l is T0 : the initial load rate of the transformer when the electric automobile is connected to the grid is avoided; m 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i;
the third calculating unit is used for determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000053
in the formula: l is C : the load rate of the line; l is C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m 2 : number of lines, M 2 Is a positive integer; beta is a i : line sensitivity to access i-point electric vehicle loads.
Compared with the closest prior art, the technical scheme provided by the invention has the following beneficial effects:
according to the technical scheme provided by the invention, the virtual energy storage capacity range of each electric automobile charging and discharging area in the wide area power distribution network is determined, and the virtual energy storage capacity distribution scheme of each electric automobile when the virtual energy storage total capacity of the electric automobiles connected with the wide area power distribution network is the maximum is determined according to the virtual energy storage capacity range of each electric automobile charging and discharging area, wherein the electric automobile charging and discharging area is divided by carrying out regional aggregation on the electric automobiles distributed in the wide area power distribution network at the same time interval, each area corresponds to one node, a specific distribution method is provided according to influence factors of each node, and reliable reference is provided for safe operation of the power grid after the electric automobiles are connected with the power distribution network.
The technical scheme provided by the invention realizes the functions of improving the access capability of renewable energy power generation of the regional power distribution network, clipping peaks and filling valleys, participating in auxiliary service and improving the quality of electric energy.
According to the technical scheme provided by the invention, the aggregation effect of charging loads of the electric automobiles attached to each access point in wide area distribution in the same time period and the influences of the voltages of all nodes and the load rates of network elements are considered, a first-order network sensitivity analysis method is adopted, and the voltage and load rate limit values of safe operation of the power distribution network specified by the related technology are referred to, so that the maximum target of the virtual energy storage total capacity of the electric automobiles connected with the power distribution network in the wide area distribution network in the time period is realized, and the calculation method can be adopted to determine the maximum allowable grid-connected electric automobile virtual energy storage total capacity of the wide area distribution network.
According to the technical scheme provided by the invention, the optimal combined distribution capacity of the electric automobile of each subarea grid-connected node is calculated in an optimized manner, so that a scheduling decision maker is helped to provide a reference scheme, the capacity of the existing power distribution network is fully utilized, the safe operation condition of the power distribution network is guaranteed not to be exceeded, and the investment cost for expanding the power distribution network is reduced.
Drawings
Fig. 1 is a flowchart of a virtual energy storage capacity allocation method for an electric vehicle according to the present invention;
fig. 2 is a structural diagram of a virtual energy storage capacity allocation method according to an embodiment of the present invention;
fig. 3 is a diagram of a virtual energy storage system based on an electric vehicle according to an embodiment of the present invention.
Detailed Description
For a better understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples.
Fig. 1 is a flowchart of a virtual energy storage capacity allocation method for an electric vehicle according to the present invention, as shown in fig. 1, including:
step S101, determining a virtual energy storage capacity range of each electric automobile charging and discharging area in a wide area power distribution network;
step S102, determining a virtual energy storage capacity distribution scheme of each electric automobile when the total virtual energy storage capacity of the electric automobiles of the wide area power distribution network connected to the power grid is maximum according to the virtual energy storage capacity range of each electric automobile in the charging and discharging area;
and S103, the electric vehicle charging and discharging areas are divided by carrying out regional aggregation on electric vehicles distributed in the same time period in the wide area power distribution network, and each area corresponds to one node.
Specifically, step S102 is to determine a virtual energy storage capacity allocation scheme for each electric vehicle when the total virtual energy storage capacity of the electric vehicle of the wide area power distribution network connected to the grid is maximum according to the virtual energy storage capacity range of each electric vehicle in the charging and discharging area, and includes:
determining the running parameters of the electric automobile when the electric automobile is connected to the grid according to the running parameters of the electric automobile when the electric automobile is not connected to the grid in the wide area power distribution network;
and determining the virtual energy storage capacity range of each node according to the operation parameters of the electric automobile during grid connection and preset operation parameter constraint conditions.
Wherein the operating parameters include: the voltage of the node, the load rate of the transformer and the load rate of the line; and maximum charge-discharge current, voltage fluctuation and flicker, voltage imbalance, short-circuit capacity.
Further, according to the running parameters when no electric vehicle is connected to the grid in the wide area distribution network, the running parameters when the electric vehicle is connected to the grid are determined, and the method comprises the following steps:
the voltage of each node when the electric automobile is connected to the grid is determined according to the following formula:
Figure BDA0001585022910000071
determining the load rate of each transformer when the electric automobile is connected to the grid by the following formula:
Figure BDA0001585022910000072
determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000073
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p is EVi : virtual energy storage capacity of node i; p EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer; l is T : the load factor of the transformer; l is T0 : the initial load rate of the transformer when the electric automobile is connected to the grid is avoided; m 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the i point; l is C : the load factor of the line; l is C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m 2 : number of lines, M 2 Is a positive integer; beta is a i : line sensitivity to access i-point electric vehicle loads.
In an embodiment, the preset operating parameter constraints include:
the voltage constraint of the node is as follows:
V min ≤V i ≤V max
the load factor constraint of the transformer is as follows:
L T ≤L Tlimit
the load rate constraint of the line is as follows:
L C ≤L Climit
in the formula: v min : a minimum value of the node voltage; v max : the maximum value of the node voltage; l is Tlimit : a critical value of the load factor of the transformer; l is a radical of an alcohol Climit : line load rate threshold.
In the embodiment, determining the virtual energy storage capacity range of each node according to the running parameters when the electric vehicle is connected to the grid and the preset running parameter constraint conditions comprises the following steps:
determining a first virtual energy storage capacity range, a second virtual energy storage capacity range and a third virtual energy storage capacity range according to the voltage of each node, the load rate of each transformer, the load rate of each line and the corresponding node voltage constraint condition, the load rate constraint condition of the transformer and the load rate constraint condition of the line when the electric automobile is connected to the grid;
and determining the virtual energy storage capacity range of each node according to the intersection of the first, second and third virtual energy storage capacity ranges.
In the embodiment, according to the virtual energy storage capacity range of each electric vehicle in the charging and discharging area, the virtual energy storage capacity allocation scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicle of the wide area power distribution network grid connection is the maximum is determined, and the scheme comprises the following steps:
determining a virtual energy storage capacity allocation scheme of the electric automobile in each node through a linear programming algorithm according to the virtual energy storage capacity range of each node and a pre-constructed objective function;
and constructing a pre-constructed objective function according to the sum of the upper limits of the virtual energy storage capacity of each node.
Wherein the objective function is shown as follows:
Figure BDA0001585022910000091
in the formula: p EVmax : virtual total energy storage capacity of the wide area network; n: the number of divided areas in the wide area network, wherein N is a positive integer; p is EVi : virtual energy storage capacity of node i.
Further, after determining the virtual energy storage capacity allocation scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide area power distribution network grid-connected is maximum, the method further comprises the following steps:
carrying out load flow simulation calculation on the virtual energy storage capacity distribution scheme of each electric automobile when the total virtual energy storage capacity is maximum;
when the voltage of each node, the load rate of the transformer and the load rate of the line all meet the preset operation parameter constraint condition, the virtual energy storage capacity allocation scheme of the electric automobile is available; otherwise, the virtual energy storage capacity allocation scheme of the electric automobile is unavailable.
And outputting the available electric vehicle capacity allocation schemes to a dispatching center.
Fig. 2 is a structural diagram of a virtual energy storage capacity allocation method in an embodiment of the present invention, and as shown in fig. 2, the method specifically includes the following steps:
1) As shown in fig. 3, a virtual energy storage system diagram based on electric vehicles is provided, which is used for performing regional aggregation on electric vehicles distributed in a wide area distribution network, and dividing the electric vehicles into a plurality of electric vehicle charging and discharging regions (EVs) Field i ) One area corresponds to one node; each zone comprises m electric vehicle charging and discharging stations (EV) Field j ) Each station can provide service (EV) for n electric vehicles Vehicle k )。
2) And updating background load data in real time, and recording the voltage of each node in the wide area distribution network and the load rate of network elements.
3) Carrying out simulation calculation analysis on the sensitivity of the power flow, wherein the specific method comprises the following steps:
(3-1) considering that when the load of the electric automobile is added to a certain node in the wide area distribution network, the voltage of all the nodes and the load rate of network elements related to the node are influenced, and the voltage of the access point i at a certain moment is approximately calculated by utilizing the first-order sensitivity of the network according to the following formula:
Figure BDA0001585022910000092
the load factor of the transformer is calculated as follows:
Figure BDA0001585022910000101
the load factor of the line is calculated as follows:
Figure BDA0001585022910000102
in the formula, V i : the voltage of node i; v i0 Is the initial voltage of the node i when no electric vehicle is connected to the grid,μ i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p EVi : virtual energy storage capacity of node i; p EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer; l is T : the load factor of the transformer; l is T0 : the initial load rate of the transformer when the electric automobile is connected to the grid is avoided; l is C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m is a group of 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i; l is C : the load rate of the line; m 2 : number of lines, M 2 Is a positive integer; beta is a i : line sensitivity to access i-point electric vehicle loads.
(3-2) carrying out power flow sensitivity analysis by using the data recorded in the step 2): the time-period voltage sensitivity factor mu, the sensitivity factor alpha of the load factor of the transformer and the sensitivity factor beta of the load factor of the line are calculated respectively.
4) According to the relevant standard regulation, the safe and stable operation conditions of the power distribution network are guaranteed as constraints:
V min ≤V i ≤V max
L T ≤L Tlimit
L C ≤L Climit
establishing a linear equation as shown in the following formula, wherein the maximum virtual energy storage total capacity of the electric automobile for realizing grid connection of the wide-area power distribution network in the time period is a target function;
Figure BDA0001585022910000103
in the formula: v i : the voltage of node i; l is T : the load factor of the transformer; l is a radical of an alcohol C : the load factor of the line; l is a radical of an alcohol Tlimit : a critical value of the load factor of the transformer; l is a radical of an alcohol Climit : a threshold value of line load rate; p is EVmax : a virtual total energy storage capacity of the wide area network; n: divided regions in a wide area networkNumber, N is a positive integer.
5) Calculating the optimal combined distribution capacity of the electric automobile of each partition grid-connected node by using a linear programming algorithm so as to determine a target function value;
6) Carrying out result verification on the data of the step 2) and the step 5):
(6-1) carrying out load flow calculation by using the data, and judging whether the calculated voltage or load rate is safe and not out of limit according to the limit value specified in the step 4);
(6-2) neither of the electric vehicles exceeds the limit, the obtained optimization scheme is available, and the available electric vehicle capacity allocation scheme is output to the dispatching center; otherwise, the optimization scheme is unavailable, and the step 2) is returned to calculate again.
7) The calculation process ends.
Based on the same concept, the invention also provides a virtual energy storage capacity distribution system of the electric automobile, which comprises the following components:
the determining module is used for determining the virtual energy storage capacity range of each electric automobile charging and discharging area in the wide area power distribution network;
the distribution module is used for determining a virtual energy storage capacity distribution scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide-area power distribution network grid-connected is maximum according to the virtual energy storage capacity range of each electric vehicle charge-discharge area;
and the division module is used for dividing the electric automobile charging and discharging areas distributed in the same time period in the wide area power distribution network by carrying out regional aggregation, and each area corresponds to one node.
Preferably, the distribution module includes:
the first determining unit is used for determining the running parameters of the electric automobile when the electric automobile is connected in the grid according to the running parameters of the electric automobile when the electric automobile is not connected in the wide area power distribution network;
and the second determining unit is used for determining the virtual energy storage capacity range of each node according to the running parameters when the electric automobile is connected to the grid and the preset running parameter constraint conditions.
Preferably, the distribution module further includes:
the first calculation unit is used for determining the voltage of each node when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000121
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p is EVi : virtual energy storage capacity of node i; p is EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer;
the second calculating unit is used for determining the load rate of each transformer when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000122
in the formula: l is T : the load factor of the transformer; l is T0 : the initial load rate of the transformer when no electric automobile is connected to the grid; m 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i;
the third calculating unit is used for determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure BDA0001585022910000123
in the formula: l is C : the load rate of the line; l is C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m is a group of 2 : number of lines, M 2 Is a positive integer; beta is a i : line sensitivity to access i-point electric vehicle loads.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (9)

1. A virtual energy storage capacity distribution method of an electric automobile is characterized by comprising the following steps:
determining a virtual energy storage capacity range of each electric vehicle charging and discharging area in a wide area power distribution network;
determining a virtual energy storage capacity distribution scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide area power distribution network grid connection is maximum according to the virtual energy storage capacity range of each electric vehicle charge and discharge area;
the electric vehicle charging and discharging areas are divided by carrying out regional aggregation on electric vehicles distributed in the wide area power distribution network at the same time period, and each area corresponds to one node;
the virtual energy storage capacity range of each electric automobile charging and discharging area in the wide area power distribution network is determined, and the method comprises the following steps:
determining the running parameters of the electric automobile when the electric automobile is connected to the grid according to the running parameters of the electric automobile when the electric automobile is not connected to the grid in the wide area power distribution network;
determining the virtual energy storage capacity range of each node according to the operation parameters of the electric vehicle during grid connection and preset operation parameter constraint conditions;
the operating parameters include: the voltage of the node, the load rate of the transformer and the load rate of the line;
the method for determining the operation parameters of the electric automobile when the electric automobile is connected to the grid according to the operation parameters of the electric automobile when the electric automobile is not connected to the grid in the wide area power distribution network comprises the following steps:
and determining the voltage of each node when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000011
determining the load rate of each transformer when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000012
determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000013
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p EVi : virtual energy storage capacity of node i; p EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer; l is T : the load factor of the transformer; l is a radical of an alcohol T0 : the initial load rate of the transformer when the electric automobile is connected to the grid is avoided; m 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i; l is a radical of an alcohol C : the load rate of the line; l is a radical of an alcohol C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m 2 : number of lines, M 2 Is a positive integer; beta is a beta i : line sensitivity to access i-point electric vehicle loads.
2. The virtual energy storage capacity allocation method according to claim 1, wherein the preset operation parameter constraints include:
the voltage constraint of the node is as follows:
V min ≤V i ≤V max
the load factor constraint of the transformer is as follows:
L T ≤L Tlimit
the load rate constraint of the line is as follows:
L C ≤L Climit
in the formula: v min : a minimum value of the node voltage; v max : the maximum value of the node voltage; l is Tlimit : a critical value of the load factor of the transformer; l is a radical of an alcohol Climit : line load rate threshold.
3. The virtual energy storage capacity allocation method according to claim 2, wherein the determining the virtual energy storage capacity range of each node according to the running parameters when the electric vehicle is connected to the grid and the preset running parameter constraint conditions includes:
determining a first virtual energy storage capacity range, a second virtual energy storage capacity range and a third virtual energy storage capacity range according to the voltage of each node, the load rate of each transformer, the load rate of each line and the corresponding node voltage constraint condition, the load rate constraint condition of the transformer and the load rate constraint condition of the line when the electric vehicle is connected to the grid;
and determining the virtual energy storage capacity range of each node according to the first, second and third virtual energy storage capacity ranges.
4. The virtual energy storage capacity allocation method according to claim 3, wherein determining the virtual energy storage capacity range of each node according to the first, second and third virtual energy storage capacity ranges comprises:
and determining the virtual energy storage capacity range of each node according to the intersection of the first, second and third virtual energy storage capacity ranges.
5. The virtual energy storage capacity allocation method according to claim 1, wherein the step of determining the virtual energy storage capacity allocation scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles connected to the wide area power distribution network is the maximum according to the virtual energy storage capacity range of each electric vehicle in the charging and discharging area comprises the following steps:
determining a virtual energy storage capacity allocation scheme of the electric automobile in each node through a linear programming algorithm according to the virtual energy storage capacity range of each node and a pre-constructed objective function;
and the pre-constructed objective function is constructed according to the virtual energy storage capacity of each node.
6. The virtual energy storage capacity allocation method according to claim 1, wherein after determining the virtual energy storage capacity allocation scheme for each electric vehicle when the total virtual energy storage capacity of the electric vehicles connected to the wide area power distribution network is the maximum, the method further comprises:
carrying out load flow simulation calculation on the virtual energy storage capacity distribution scheme of each electric automobile when the total virtual energy storage capacity is maximum;
when the voltage of each node, the load rate of the transformer and the load rate of the line all meet the preset operation parameter constraint condition, the virtual energy storage capacity allocation scheme of the electric automobile is available; otherwise, the virtual energy storage capacity allocation scheme of the electric automobile is unavailable.
7. The virtual energy storage capacity allocation method according to claim 6, wherein the available electric vehicle capacity allocation plans are output to the dispatch center.
8. The virtual energy storage capacity allocation method according to claim 5, wherein the objective function is expressed by the following formula:
Figure FDA0003758705770000031
in the formula: p is EVmax : a virtual total energy storage capacity of the wide area network; n: the number of divided areas in the wide area network, wherein N is a positive integer; p is EVi : virtual energy storage capacity of node i.
9. A virtual energy storage capacity distribution system of an electric vehicle, characterized by comprising:
the determining module is used for determining the virtual energy storage capacity range of each electric automobile charging and discharging area in the wide area power distribution network;
the distribution module is used for determining a virtual energy storage capacity distribution scheme of each electric vehicle when the total virtual energy storage capacity of the electric vehicles of the wide area power distribution network is the maximum according to the virtual energy storage capacity range of each electric vehicle in the charging and discharging area;
the dividing module is used for dividing the electric automobile charging and discharging areas distributed in the same time period in a wide area power distribution network by carrying out regional aggregation, and each area corresponds to one node;
the distribution module comprises:
the first determining unit is used for determining the running parameters of the electric automobile when the electric automobile is connected in the grid according to the running parameters of the electric automobile when the electric automobile is not connected in the wide area power distribution network;
the second determining unit is used for determining the virtual energy storage capacity range of each node according to the running parameters of the electric automobile during grid connection and preset running parameter constraint conditions;
the distribution module further comprises:
the first calculation unit is used for determining the voltage of each node when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000041
in the formula, V i : the voltage of node i; v i0 : the initial voltage of the node i when the electric automobile is connected to the grid is avoided; mu.s i : the sensitivity of the voltage of the point i to the load of the electric automobile connected to the point i; mu.s ij : the sensitivity of the voltage at the point i to the load of the electric automobile connected to the point j; p EVi : virtual energy storage capacity of node i; p EVj : virtual energy storage capacity of node j; n: the number of nodes, N is a positive integer;
the second calculating unit is used for determining the load rate of each transformer when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000042
in the formula: l is T : the load factor of the transformer; l is T0 : electric-free automobile grid connection time varyingInitial load rate of the transformer; m 1 : number of transformers, M 1 Is a positive integer; alpha is alpha i : the sensitivity of the transformer to the load of the electric automobile connected to the point i;
the third calculating unit is used for determining the load rate of each line when the electric automobile is connected to the grid through the following formula:
Figure FDA0003758705770000043
in the formula: l is C : the load rate of the line; l is C0 : the initial load rate of the line when the electric automobile is connected to the grid is avoided; m is a group of 2 : number of lines, M 2 Is a positive integer; beta is a beta i : line sensitivity to access i-point electric vehicle loads.
CN201810169752.9A 2018-02-28 2018-02-28 Virtual energy storage capacity distribution method and system for electric automobile Active CN108462195B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810169752.9A CN108462195B (en) 2018-02-28 2018-02-28 Virtual energy storage capacity distribution method and system for electric automobile

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810169752.9A CN108462195B (en) 2018-02-28 2018-02-28 Virtual energy storage capacity distribution method and system for electric automobile

Publications (2)

Publication Number Publication Date
CN108462195A CN108462195A (en) 2018-08-28
CN108462195B true CN108462195B (en) 2022-10-25

Family

ID=63216961

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810169752.9A Active CN108462195B (en) 2018-02-28 2018-02-28 Virtual energy storage capacity distribution method and system for electric automobile

Country Status (1)

Country Link
CN (1) CN108462195B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
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
CN113364015B (en) 2021-05-14 2024-01-09 华为数字能源技术有限公司 Energy storage system and related method

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103840521B (en) * 2014-02-27 2016-08-17 武汉大学 Extensive electric automobile based on optimal load flow optimizes charge-discharge system and method
CN106058904B (en) * 2016-06-30 2022-04-29 全球能源互联网研究院 Capacity matching method for charging pile of energy storage type electric automobile

Also Published As

Publication number Publication date
CN108462195A (en) 2018-08-28

Similar Documents

Publication Publication Date Title
Zheng et al. A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid
Jian et al. Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid
Kumar et al. V2G capacity estimation using dynamic EV scheduling
KR101566715B1 (en) Efficient electric vehicles charging algorithm with priority index method
CN109742779B (en) Distributed energy storage scheduling method and device
JP5987241B2 (en) Charge control system
KR101769776B1 (en) System and method for Frequency Control
Kumar et al. A review on integration of electric vehicles into a smart power grid and vehicle-to-grid impacts
He et al. An optimal charging/discharging strategy for smart electrical car parks
CN111016721B (en) Local ordered charging strategy for electric automobile meeting three-phase balance of platform area
Xie et al. A novel dispatching control strategy for EVs intelligent integrated stations
CN111619393A (en) User-oriented orderly charging control method for electric automobile in transformer area
Aunedi et al. Efficient system integration of wind generation through smart charging of electric vehicles
CN108462195B (en) Virtual energy storage capacity distribution method and system for electric automobile
Faddel et al. An automated charger for large-scale adoption of electric vehicles
CN110829474B (en) Method and system for supporting dynamic security of power grid by using big data intelligent energy storage
KR20130092707A (en) System and control method for community energy system
CN112886623A (en) Energy storage converter VSG mode energy management coordination control method and system
Zhang et al. A vehicle-to-grid based reactive power dispatch approach using particle swarm optimization
El-Zonkoly et al. Optimal allocation, sizing and energy management of PHEV parking lots in distribution system
CN113381426B (en) Capacity configuration method of flywheel energy storage device, terminal and storage medium
Xie et al. Supplementary automatic generation control using electric vehicle battery swapping stations
Wu et al. Optimizing EV cluster contribution for vehicle-to-grid (V2G) frequency regulation
Shaaban et al. PEVs real-time coordination in smart grid based on moving time window
Zhou et al. The state-of-art of the EV charging control strategies

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant