CN111523734A - Electric automobile ordered charging optimization method - Google Patents
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- 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
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Abstract
The invention provides an electric automobile ordered charging optimization method, which comprises the following steps: s1, selecting a power distribution network accessed by an electric automobile; s2, acquiring impedance data of all branches of the power distribution network; s3, establishing an electric vehicle ordered charging optimization model by combining the impedance data acquired in the step S2 and taking the minimum grid loss of the power distribution network as a target and the node power of the power distribution network, the charging power of the electric vehicle and the node voltage as constraint conditions; and S4, solving the electric automobile ordered charging optimization model to obtain an electric automobile ordered charging scheme. The method provided by the invention overcomes the adverse effects of the increase of the network loss of the power distribution network and the charging impedance plug caused by the disordered charging behavior of the conventional electric charging automobile, is beneficial to standardizing the charging behavior of the electric automobile, reduces the network loss of the power distribution network and improves the power supply quality of the power distribution network.
Description
Technical Field
The invention relates to the technical field of electric automobile charging, in particular to an orderly charging optimization method for an electric automobile.
Background
The electric automobile is highly concerned and massively invested in various countries as an important clean energy power, the market scale is rapidly increased, the sales volume and the holding capacity of the new energy automobile in China are increased by hundreds of times, meanwhile, a charging network is also in a rapid development period, China becomes the largest global charging pile market, and large-scale charging infrastructure is put into operation, so that new opportunities and challenges are brought to the development of a power distribution network.
Firstly, the electric automobile can be connected to the power grid in any time period through an interface of a charging pile on the market to cause disordered charging of the electric automobile, and when the number of the electric automobiles is large, the phenomenon of charging impedance blockage is caused by the shortage of charging facility throwing speed and management; secondly, the disordered charging behavior of the electric automobile is easy to load in a load peak period, which causes the adverse effect of increasing the network loss of the power distribution network and influences the power supply quality of the power distribution network.
Therefore, in the process of popularization of the electric automobile, the research on the ordered charging optimization method of the electric automobile is of great significance.
Disclosure of Invention
In order to overcome the adverse effects of the increase of the network loss of the power distribution network and the charging of the impedance plug caused by the disordered charging behavior of the conventional electric charging automobile, the invention provides the ordered charging optimization method for the electric automobile, which is used for reducing the network loss of the power distribution network and improving the power supply quality of the power distribution network.
The present invention aims to solve the above technical problem at least to some extent.
In order to achieve the technical effects, the technical scheme of the invention is as follows:
an orderly charging optimization method for an electric vehicle at least comprises the following steps:
s1, selecting a power distribution network accessed by an electric automobile;
s2, acquiring impedance data of all branches of the power distribution network;
s3, establishing an electric vehicle ordered charging optimization model by combining the impedance data acquired in the step S2 and taking the minimum grid loss of the power distribution network as a target and the node power of the power distribution network, the charging power of the electric vehicle and the node voltage as constraint conditions;
and S4, solving the electric automobile ordered charging optimization model to obtain an electric automobile ordered charging scheme.
Preferably, the position of the electric vehicle access to the distribution network node is known.
Almost all electric vehicles are charged by charging piles at present, and the positions of parking spaces and the charging piles in a power distribution network are basically fixed, so that the positions of the electric vehicles connected to nodes of the power distribution network are determined and the site selection optimization of the charging piles of the electric vehicles is not involved.
Preferably, the electric vehicles connected to the same node of the power distribution network have the same charging state within the same time interval Δ t, that is, are charged simultaneously and leave the charging pile simultaneously.
Preferably, the impedances of all branches of the power distribution network of step S2 are constant at the time. The impedance includes the resistance and reactance of the line, i.e. both the resistance and the reactance are constant at all times.
Preferably, the bus nodes of the distribution network connecting the substation are balance nodes, and the distribution network nodes except the bus nodes are PQ nodes.
In the method, the power distribution network is supplied by the transformer substation, the fluctuation of an external power supply is not considered, and on the premise that the capacity of an external power grid is large enough, the bus node of the power distribution network connected with the transformer substation is a balance node, so that the convergence of load flow calculation in the subsequent optimization process is ensured.
Preferably, the expression of the objective function is:
wherein lines represents the total number of branches of the power distribution network; l represents the l-th branch, and T represents the total charging scheduling time of the electric automobile; Δ t represents a time interval; rlRepresenting the resistance of the first branch, Il,tThe branch current value of the l-th branch at time t is shown.
Preferably, the constraint condition is that the power distribution network node power satisfies at any time:
wherein, PrmRepresenting the injection active power of the node m of the power distribution network at any moment; qrmRepresents the reactive power injected by the node m of the distribution network at any moment; rm-1Representing the resistance of the branch between node m-1 and node m; xm-1Represents the reactance of the branch between node m-1 and node m; pm-1Is at random for node m-1The active load at a moment; qm-1Is the reactive load of the node m-1 at any moment; vm-1Is the node voltage of node m-1; pmRepresenting the active load value of a node m of the power distribution network at any moment; qmRepresenting the reactive load value of a node m of the power distribution network at any moment; node(s)m,tRepresenting the state of the electric vehicle at the node m, when the electric vehicle is accessed at the node m, the nodem,tTaking 1; otherwise, the nodem,tTaking 0; pEVm,tRepresenting the charging power of the electric vehicle at the access node m.
Here, the active power and the reactive power of the nodes of the power distribution network need to satisfy the requirement of power balance, and the electric vehicle is equivalent to the active load of the nodes of the power distribution network for the power distribution network and does not have the influence of increase and decrease on the original reactive load of the power distribution network, so when the power of the nodes of the power distribution network is considered to be balanced by the active power, the charging power of the electric vehicle needs to be included, but the equation of the original reactive power balance of the nodes of the power distribution network is not influenced.
Preferably, the charging power of the electric vehicle at the access node m satisfies:
0≤MPm,t≤K
where K denotes an upper limit value of the charging power of the electric vehicle at the access node m.
Here, the charging power of the electric vehicle at the access node m is a load with respect to the power distribution network, so the charging power of the electric vehicle is at least zero with respect to the power distribution network, i.e., the charging power of the electric vehicle is 0 when the electric vehicle is not charging away, on the other hand, the electric vehicle itself corresponds to an energy storage battery, there is an upper limit of the maximum charging power, i.e., K, and the charging power of the electric vehicle at the access node m is continuously adjustable between 0 and K.
Preferably, the node voltage in the constraint is satisfied at any time:
Vmin,m≤Vm≤Vmax,m
wherein, Vmin,mRepresents a lower limit value of the node voltage of the node m; vmRepresents the node voltage value of the node m; vmax,mRepresents the upper limit of the node voltage of the node m.
Preferably, the time interval Δ T is 1 hour and the electric vehicle T is 24 hours.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention provides an electric automobile ordered charging method, which is characterized in that an electric automobile ordered charging optimization model taking the minimum grid loss of a power distribution network as a target and taking the node power of the power distribution network, the charging power of an electric automobile and the node voltage as constraint conditions is established and solved to obtain an electric automobile ordered charging scheme, the adverse effects of the increase of the grid loss of a power distribution network and the charging impedance plug caused by the disordered charging behavior of the conventional electric charging automobile are overcome, the grid loss of the power distribution network is favorably reduced, and the power supply quality of the power distribution network is improved.
Drawings
FIG. 1 is a schematic flow chart of an electric vehicle ordered charging optimization method provided by the invention;
FIG. 2 is a schematic diagram of a framework of a power distribution network to which selected electric vehicles are connected according to an embodiment of the present invention;
FIG. 3 is a schematic daily load curve for a distribution network without electric vehicle access as set forth in an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating a comparison between a load curve of the electric vehicle, which is provided in the embodiment of the present invention and has no electric vehicle access to the power distribution network during the charging period, and a load curve after the ordered charging optimization;
fig. 5 is a schematic diagram showing a daily load curve of the power distribution network, a load curve after the electric vehicle is connected into the ordered charging and optimized, and a load curve after the non-optimized unordered charging, which are provided in the embodiment of the present invention.
Fig. 6 is a schematic diagram showing a comparison of power distribution network loss curves in three scenarios including no electric vehicle access, ordered charging optimization after electric vehicle access, and unordered charging optimization after electric vehicle access, proposed in the embodiment of the present invention.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
it will be understood by those skilled in the art that certain well-known illustrations in the drawings may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 1, a schematic flow chart of an orderly charging optimization method for an electric vehicle according to the present invention includes:
s1, selecting a power distribution network accessed by an electric automobile;
in this embodiment, referring to fig. 2, the framework structure of the distribution network to which the electric vehicle is connected is an IEEE33 node network connection diagram, the total active power amount of the distribution network at the peak time of daily load is 3715.0kW, the total reactive power amount is 2300.0kvar, the reference capacity is 100MVA, the reference voltage is 12.66kV, and after per unit, the node voltage V ismUpper limit value V ofmax,m1.05pu is taken, lower limit value Vmin,mAnd taking 0.95pu, wherein the electric vehicles connected to the same node of the power distribution network have the same charging state within the same time interval delta t, namely, the electric vehicles are charged simultaneously and leave the charging pile simultaneously, and the number of the electric vehicles connected to the power distribution network is set to be 1600. As shown in fig. 2, since the distribution network is supplied by the substation, without considering the fluctuation of the external power supply, and on the premise that the capacity of the external power grid is large enough, the bus node of the distribution network connected to the substation is a balanced node, which ensures the convergence of the load flow calculation in the subsequent optimization process, therefore, the bus node 0 of the distribution network is a balanced node, and the other distribution network nodes except the bus node: the nodes 1 to 32 are all PQ nodes, 50 electric automobiles are placed in each PQ node, the upper limit value K of the charging power of each electric automobile is 1.8kW, and the charging power of each electric automobile is continuously adjustable.
S2, acquiring impedance data of all branches of the power distribution network; referring to table 1, the impedance data for all the branches of the distribution network, in this embodiment, the impedance of all the branches of the distribution network is constant at all times.
TABLE 1
| Front node | Rear node | Branch impedance | Front node | Rear | Branch impedance | |
| 0 | 1 | 0.0922+j0.047 | 16 | 17 | 0.3720+j0.5740 | |
| 1 | 2 | 0.4930+j0.2511 | 1 | 18 | 0.1640+j0.1565 | |
| 2 | 3 | 0.3660+j0.1864 | 18 | 19 | 1.5042+j1.3554 | |
| 3 | 4 | 0.3811+j0.1941 | 19 | 20 | 0.4095+j0.4784 | |
| 4 | 5 | 0.8190+j0.7070 | 20 | 21 | 0.7089+j0.9373 | |
| 5 | 6 | 0.1872+j0.6188 | 2 | 22 | 0.4512+j0.3083 | |
| 6 | 7 | 0.7114+j0.2351 | 22 | 23 | 0.8980+j0.7091 | |
| 7 | 8 | 1.0300+j0.7400 | 23 | 24 | 0.8960+j0.7011 | |
| 8 | 9 | 1.0440+j0.7400 | 5 | 25 | 0.2030+j0.1034 | |
| 9 | 10 | 0.1966+j0.0650 | 25 | 26 | 0.2842+j0.1447 | |
| 10 | 11 | 0.3744+j0.1238 | 26 | 27 | 1.0590+j0.9337 | |
| 11 | 12 | 1.4680+j1.1550 | 27 | 28 | 0.8042+j0.7006 | |
| 12 | 13 | 0.5416+j0.7129 | 28 | 29 | 0.5075+j0.2585 | |
| 13 | 14 | 0.5910+j0.5260 | 29 | 30 | 0.9744+j0.9630 | |
| 14 | 15 | 0.7463+j0.5450 | 30 | 31 | 0.3105+j0.3619 | |
| 15 | 16 | 1.2890+j1.7210 | 31 | 32 | 0.3410+j0.5362 |
S3, combining the branch impedance data collected in the step S2 and shown in the table 1, aiming at the minimum grid loss of the power distribution network, and establishing an electric vehicle ordered charging optimization model by taking the node power of the power distribution network, the charging power of the electric vehicle and the node voltage as constraint conditions;
in this embodiment, the expression of the objective function is:
wherein lines represents the total number of branches of the power distribution network; l represents the l-th branch, and T represents the total charging scheduling time of the electric automobile; Δ t represents a time interval; rlRepresenting the resistance of the first branch, Il,tThe branch current value of the ith branch at the time T is represented, in the embodiment, Δ T is 1 hour, T represents the total scheduling time of the electric vehicle, and 24 hours a day is taken;
the constraint conditions are as follows:
the power of the nodes of the power distribution network meets the following conditions at any time:
wherein, PrmRepresenting the injection active power of the node m of the power distribution network at any moment; qrmRepresents the reactive power injected by the node m of the distribution network at any moment; rm-1Representing the resistance of the branch between node m-1 and node m; xm-1Represents the reactance of the branch between node m-1 and node m; pm-1Is the active load of the node m-1 at any moment; qm-1Is the reactive load of the node m-1 at any moment; vm-1Is the node voltage of node m-1; pmRepresenting the active load value of a node m of the power distribution network at any moment; qmRepresenting the reactive load value of a node m of the power distribution network at any moment; node(s)m,tRepresenting the state of the electric vehicle at the node m, when the electric vehicle is accessed at the node m, the nodem,tTaking 1; otherwise, the nodem,tTaking 0; pEVm,tRepresenting the charging power of the electric vehicle at the access node m.
Since 50 electric vehicles are accessed to PQ nodes represented by nodes 1 to 32 except for node 0 in the power distribution network, node values of the nodes 1 to 32 all take 1; the node voltage satisfies at any time:
0.95pu≤Vm≤1.05pu
fig. 3 is a schematic diagram of a daily load curve of the power distribution network without electric vehicle access in the embodiment of the present invention, where the ordinate is an active load value of the power distribution network and the abscissa is time, it can be known from fig. 3 that a corresponding daily load curve of the power distribution network without electric vehicle access has a serious peak-to-valley difference due to uneven power consumption time of a user;
and S4, solving the electric automobile ordered charging optimization model to obtain an electric automobile ordered charging scheme.
The method comprises the following steps of establishing an electric vehicle ordered charging optimization model as a nonlinear optimization planning model by taking the minimum grid loss of a power distribution network as a target and taking the node power of the power distribution network, the charging power of an electric vehicle and the node voltage as constraint conditions, calling a SNOPT nonlinear optimization solver based on a sequence quadratic programming method through a GAMS (gamma-ray modeling system) platform to solve the electric vehicle ordered charging optimization model, and solving the charging power of the electric vehicle connected to nodes 1-32 of the power distribution network in 24 hours a day when the grid loss of a target function power distribution network is minimum to obtain the charging power of the electric vehicle in 21: charge in time period 00-6:00, while charge in 6: the charging power of the time period of 00-21:00 is 0, namely the electric automobile adopts the following steps of 6: no charging during the time period 00-21:00, but at 21: when the charging is carried out in the time period of 00-6:00, the network loss of the power distribution network is the minimum. Further, the electric vehicle shown in fig. 4 is characterized in that 21: a schematic comparison diagram of a load curve of a power distribution network without electric vehicle access and a load curve of an electric vehicle accessed and optimized by ordered charging in a charging time period of 00-6:00 is shown in fig. 4, and the electric vehicle is charged in the time period of 21:00-6:00, the peak-valley difference of the power distribution network is obviously reduced compared with that of the electric vehicle without electric vehicle access, and the electric vehicle is charged in the ordered mode in the time period of 21:00-6:00, so that the load fluctuation of the original power distribution network in the time period is inhibited, and the network loss can be further reduced; fig. 5 is a schematic diagram showing a comparison between a daily load curve of a power distribution network, a daily load curve after an electric vehicle is connected and optimized in order charging and a load curve after the electric vehicle is connected and unoptimized and unordered charging, which is proposed in an embodiment of the present invention, and referring to fig. 5, when the electric vehicle is not optimized and is charged in an electricity consumption peak period but is charged in an electricity consumption peak-valley period, a load peak-valley difference of the power distribution network is increased, and when the electric vehicle is optimized and charged in order, and when the load of the power distribution network is in a valley period, as shown in fig. 4, early: 00, the charging power of the electric automobile is large, and when the load of the power distribution network is in a peak period, such as 21:00, the charging power of the electric automobile is low, and through orderly charging optimization, the charging access of the electric automobile can always distribute peak-valley fluctuation of network load, so that the network loss is reduced, the power supply quality of the power distribution network is improved, and the influence of the access of the electric automobile on the power distribution network is reduced.
Table 2 shows the ordered charging period 21 obtained by solving the ordered charging optimization model of the electric vehicle in this embodiment: table 3 shows charging power and grid loss data of electric vehicles at all nodes in each time interval between 00 and 6:00, at 21: and (5) a charging power and grid loss table of the electric automobile in each time interval without sequential charging optimization between 00 and 6: 00.
TABLE 2
| Time of day | Charging power/MW | Loss on line/MW |
| 21:00 | 0.152 | 0.167 |
| 22:00 | 1 | 0.169 |
| 23:00 | 0.784 | 0.190 |
| 0:00 | 0.792 | 0.193 |
| 1:00 | 1.375 | 0.215 |
| 2:00 | 1.293 | 0.225 |
| 3:00 | 1.386 | 0.237 |
| 4:00 | 1.967 | 0.261 |
| 5:00 | 2.145 | 0.254 |
| 6:00 | 2.322 | 0.255 |
TABLE 3
| Time of day | Charging power/MW | Loss on line/MW |
| 21:00 | 0.821 | 0.326 |
| 22:00 | 0.982 | 0.320 |
| 23:00 | 1.562 | 0.300 |
| 0:00 | 2.062 | 0.280 |
| 1:00 | 2.213 | 0.254 |
| 2:00 | 2.156 | 0.255 |
| 3:00 | 2.295 | 0.260 |
| 4:00 | 0 | 0.275 |
| 5:00 | 0 | 0.277 |
| 6:00 | 0 | 0.281 |
For more visual display, the power distribution network is optimized by orderly charging after no electric automobile is accessed and optimized by unordered charging after the electric automobile is accessed, and is 21 under three scenes of: a comparison graph of the power distribution network loss curves of 00-6:00 is shown in fig. 6, and it can be seen from fig. 6 that when the electric vehicle is charged, the charging load of the electric vehicle will cause the network loss of the power distribution network to increase. And under the scene of non-optimized unordered charging, the network loss is obviously increased, and the total network loss obtained by the optimized charging scheme is reduced by a lot compared with the total network loss of the non-optimized charging scheme. The optimized charging scheme utilizes the night electricity utilization valley period for charging, reaches larger charging power when the electricity consumption is minimum, avoids the daytime electricity utilization peak period, and on the other hand, utilizes the reduction of the network loss as an optimization target, effectively realizes the purpose of reducing the load peak valley difference of the power distribution network, and improves the power supply quality of the power distribution network.
Obviously, the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and the expressions of "front" and "rear" nodes in the table are only illustrated with reference to the positions of the drawings, and are not to be construed as limiting the patent; other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. An orderly charging optimization method for an electric vehicle is characterized by at least comprising the following steps:
s1, selecting a power distribution network accessed by an electric automobile;
s2, acquiring impedance data of all branches of the power distribution network;
s3, establishing an electric vehicle ordered charging optimization model by combining the impedance data acquired in the step S2 and taking the minimum grid loss of the power distribution network as a target and the node power of the power distribution network, the charging power of the electric vehicle and the node voltage as constraint conditions;
and S4, solving the electric automobile ordered charging optimization model to obtain an electric automobile ordered charging scheme.
2. The ordered charging optimization method for the electric vehicle according to claim 1, wherein the position of the node of the electric vehicle connected to the power distribution network is determined to be known.
3. The ordered charging optimization method for the electric vehicles according to claim 1, wherein the electric vehicles connected to the same node of the power distribution network have the same charging state within the same time interval Δ t.
4. The method for optimizing ordered charging of electric vehicles according to claim 1, wherein the impedances of all branches of the power distribution network are constant at the time of step S2.
5. The ordered charging optimization method for the electric automobile according to claim 1, wherein bus nodes of a power distribution network connected with a substation are balance nodes, and power distribution network nodes except the bus nodes are PQ nodes.
6. The method for optimizing ordered charging of the electric vehicle according to claim 1, wherein the expression of the objective function is as follows:
wherein lines represents the total number of branches of the power distribution network; l represents the l-th branch, and T represents the total charging scheduling time of the electric automobile; Δ t represents a time interval; rlRepresenting the resistance of the first branch, Il,tThe branch current value of the l-th branch at time t is shown.
7. The ordered charging optimization method for the electric vehicle according to claim 6, wherein the constraint condition is that the power of the nodes of the power distribution network satisfies the following conditions at any time:
wherein, PrmRepresenting the injection active power of the node m of the power distribution network at any moment; qrmRepresents the reactive power injected by the node m of the distribution network at any moment; rm-1Representing the resistance of the branch between node m-1 and node m; xm-1Represents the reactance of the branch between node m-1 and node m; pm-1Is the active load of the node m-1 at any moment; qm-1Is the reactive load of the node m-1 at any moment; vm-1Is the node voltage of node m-1; pmRepresenting the active load value of a node m of the power distribution network at any moment; qmRepresenting the reactive load value of a node m of the power distribution network at any moment; node(s)m,tRepresenting the state of the electric vehicle at the node m, when the electric vehicle is accessed at the node m, the nodem,tTaking 1; otherwise, the nodem,tTaking 0;
representing the charging power of the electric vehicle at the access node m.
8. The ordered charging optimization method for the electric automobile according to claim 7, wherein the charging power of the electric automobile at the access node m satisfies the following conditions:
0≤MPm,t≤K
where K denotes an upper limit value of the charging power of the electric vehicle at the access node m.
9. The ordered charging optimization method for the electric automobile according to claim 7, wherein the node voltage in the constraint condition is satisfied at any time:
Vmin,m≤Vm≤Vmax,m
wherein, Vmin,mRepresents a lower limit value of the node voltage of the node m; vmRepresents the node voltage value of the node m; vmax,mRepresents the upper limit of the node voltage of the node m.
10. The method for optimizing ordered charging of the electric vehicle as claimed in claim 5, wherein the time interval Δ T is 1 hour, and the total scheduled charging time T of the electric vehicle is 24 hours.
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