CN203014424U - Electric automobile charging facility proportion configuration system - Google Patents
Electric automobile charging facility proportion configuration system Download PDFInfo
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- CN203014424U CN203014424U CN 201220662844 CN201220662844U CN203014424U CN 203014424 U CN203014424 U CN 203014424U CN 201220662844 CN201220662844 CN 201220662844 CN 201220662844 U CN201220662844 U CN 201220662844U CN 203014424 U CN203014424 U CN 203014424U
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Abstract
The utility model discloses an electric automobile charging facility proportion configuration system. The electric automobile charging facility proportion configuration system comprises a local measuring and statistical unit and an integration system, wherein the local measuring and statistical unit comprises a power measuring circuit, a transmission module, a mileage acquisition wireless gateway and an ARM9 statistical and output circuit, and the integration system is used for calculating optimum configuration proportions of charging facilities in various future distribution network areas. The electric automobile charging facility proportion configuration system takes an optimum integration index of a total distribution network load as an object, carries out proportion configuration for different charging modes of electric automobiles and can acquire the optimum proportion configuration of charging facilities in combination with charging facility capacity data, so the electric automobile charging facility proportion configuration system has properties of more accurate and greater efficiency and can carry out the proportion configuration according to practical conditions of different areas.
Description
Technical field
The utility model relates to a kind of based on the electric vehicle charging electro-technical field, relates in particular to a kind of charging electric vehicle facility proportional arrangement system.
Background technology
Along with the enhancing of social environment consciousness and the rise of gas price, the development of new-energy automobile receives people's concern gradually, and electric automobile has become the main direction of contemporary development of automobile; Simultaneously the charging electric vehicle communal facility also will increase year by year, and the coming years, the electric automobile field will obtain tremendous development.Electric automobile charging station for the electric automobile operation provides energy supplement, is the necessary important foundation auxiliary facility of Development of EV, so the construction of charging station communal facility is the prerequisite that electric automobile is popularized on a large scale.
Can the factor that the electric automobile charging station layout impacts be comprised: the total demand of electric vehicle charging electric weight, the charging modes of electric automobile operational mode and electric automobile.Only have the charge power of electric automobile to reach certain scale, charging station just may be realized layouting on a large scale economically.And the power demand of electric automobile and its recoverable amount and daily travel, unit mileage energy consumption level etc. are closely related.Simultaneously, under different operational modes electric automobile self continual mileage and charging interval are required also different, thereby affect the selection of the mode of charging, consumption, charging station construction mode and the power demand of electric energy.Therefore, according to the difference of dissimilar charging electric vehicle behavior, the hierarchical classification of research electric automobile is very necessary.In addition, the charging behavior of the electric automobile of different charging modes not only can affect the load curve of distribution, and also can distribute to the construction of corresponding electrically-charging equipment simultaneously impacts.
Ubiquitous charging modes comprises normal charge and two kinds of patterns of quick charge now: normal charge adopts constant voltage or the constant current charge of little electric current, charger and installation cost are lower, but the charging interval is longer, can take full advantage of the useful life that the electric power low-valley interval charges and improves charge efficiency and prolongation battery; Quick charge provides charging service as electric automobile at short notice take larger electric current, and the charging interval is short, but charge efficiency is lower, and corresponding work and installation cost higher.As seen the electric automobile proportional arrangement of studying different charging modes is the key of research charging electric vehicle facility proportional arrangement.
Yet the configuration of charging electric vehicle facility ratio at present, generally obtain according to distribution network planning, owing to not considering the impact of different charging modes on the electric vehicle charging electrical power, the configuration mode of existing charging electric vehicle facility ratio, its accuracy and allocative efficiency are all lower; Therefore providing a kind of can carry out the system of configuration automatically to charging electric vehicle facility ratio, becomes those skilled in the art's technical issues that need to address.
The utility model content
In view of this, the utility model embodiment provides that a kind of accuracy is higher, the better charging electric vehicle facility of efficient proportional arrangement method and system.
For achieving the above object, the utility model embodiment provides following scheme:
A kind of charging electric vehicle facility proportional arrangement system, this system comprises: local measurement and statistic unit, described local measurement and statistic unit comprise:
Gather local Vehicular charging power information, and with the power-measuring circuit of this power information output;
Be connected with described power-measuring circuit, receive described power information, and export the transport module of described power information;
Gather daily travel information, calculate daily travel expectation and variance, and the output daily travel expectation of calculating and the mileage collection radio network gateway of variance information;
Gathering radio network gateway with described transport module and described mileage respectively is connected, receive described power information, and described daily travel expectation and variance information, by the expectation of described charge power information and described daily travel and variance information are added up, obtain local charging station and begin expectation and the variance information constantly of charging, and export described begin the to charge expectation in the moment and ARM9 statistics and the output circuit of variance information;
be connected with described ARM9 statistics and output circuit, receive described expectation and the variance information constantly of charging that begins, begin according to a plurality of local charging stations expectation and the variance yields constantly that charge, electrically-charging equipment areally-distributed data and electric automobile increase the charge power demand information that the scale data are calculated distribution zone corresponding to described a plurality of local charging stations, determine this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in this distribution zone, calculate the indices of the following Distribution Network Load Data curve in this zone, ratio according to the different charging modes of indices configuration electric automobile, calculate the integrated system of each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
Wherein, described integrated system comprises:
Increase according to a plurality of local charging stations begin to charge expectation constantly and variance yields, electrically-charging equipment areally-distributed data and electric automobile the first treatment facility that the scale data are calculated the charge power demand information in distribution zone corresponding to described a plurality of local charging stations;
Be connected with described the first treatment facility, determine the second treatment facility of this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in described distribution zone;
Be connected with described the second treatment facility, calculate the 3rd treatment facility of the indices of this following Distribution Network Load Data curve in distribution zone;
Be connected with described the 3rd treatment facility, manage equipment everywhere according to the of the ratio of the different charging modes of indices configuration electric automobile;
With described everywhere reason equipment be connected, calculate the 5th treatment facility of each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
Wherein, described transport module unit comprises: Double Port Random Memory RAM, and complex programmable logic device (CPLD)/Field Programmable Gate Array FPGA translation interface.
Wherein, described ARM9 statistics and output circuit are the S3C2440A chip.
Wherein, described power-measuring circuit, transport module, mileage gather between radio network gateway and ARM9 statistics and output circuit and adopt the Ethernet transmission technology to communicate.
Wherein, the included treatment facility of described integrated system is IPC-810 industrial computer host-processor.
Based on technique scheme, the utility model embodiment provides charging electric vehicle facility proportional arrangement system is by the synergy of local measurement and statistic unit and integrated system, realized the automatic configuration of charging electric vehicle facility ratio, and the Different Effects of the different charge power demands that the utility model embodiment causes according to the different charging modes of electric automobile to the Distribution Network Load Data curve proposes four load curve indexs for assessment of the impact on the Distribution Network Load Data curve under the different proportion configuration of different charging modes electric automobiles.Then combined charge facility capacity data are carried out proportional arrangement to the construction of following electrically-charging equipment.This configuration-system is more accurate, efficient is better, and can carry out proportional arrangement according to the actual conditions of each different regions.Can show in real time data and memory function is arranged, facilitating data query and management; According to the moon statistics, year statistics, the further concrete configuration of statistical research charging electric vehicle facility ratio.
Description of drawings
In order to be illustrated more clearly in the utility model embodiment or technical scheme of the prior art, the below will do to introduce simply to the accompanying drawing of required use in embodiment or description of the Prior Art, apparently, accompanying drawing in the following describes is only embodiment more of the present utility model, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
The structured flowchart of Fig. 1 provides for the utility model embodiment charging electric vehicle facility proportional arrangement system;
The structured flowchart of the integrated system that Fig. 2 provides for the utility model embodiment;
Another structured flowchart of the integrated system that Fig. 3 provides for the utility model embodiment;
The structured flowchart of Fig. 4 provides for the utility model embodiment electric quantity acquisition unit;
The ARM9 statistics that Fig. 5 provides for the utility model embodiment and the structured flowchart of output circuit;
The flow chart of a kind of charging electric vehicle facility proportional arrangement method that Fig. 6 provides for the utility model embodiment;
The flow chart of the prediction of electric automobile power demand, Distribution Network Load Data curve prediction and index calculating method that Fig. 7 provides for utility model embodiment.
Embodiment
Below in conjunction with the accompanying drawing in the utility model embodiment, the technical scheme in the utility model embodiment is clearly and completely described, obviously, described embodiment is only the utility model part embodiment, rather than whole embodiment.Based on the embodiment in the utility model, those of ordinary skills are not making the every other embodiment that obtains under the creative work prerequisite, all belong to the scope of the utility model protection.
The structured flowchart of Fig. 1 provides for the utility model embodiment charging electric vehicle facility proportional arrangement system, as shown in Figure 1, charging electric vehicle facility proportional arrangement system comprises: local measurement and statistic unit 1 and integrated system 2.Local measurement and statistic unit 1 comprise: power-measuring circuit 01, transport module 02, mileage gather radio network gateway 03 and ARM9 statistics and output circuit 04.
Wherein, power-measuring circuit 1 sends this charge power information to transport module 02 according to the charge power information of the local vehicle of the information gatherings such as three-phase and neutral point current, three-phase and neutral point voltage;
Power-measuring circuit 1 is connected with transport module 02, optionally, transport module 02 can comprise: dual port RAM (random access memory, random asccess memory) transport module, with CPLD(ComplexProgrammable Logic Device), CPLD)/FPGA(Field-Programmable Gate Array, field programmable gate array) translation interface.Optionally, transport module 02 can pass through the dual port RAM transport module, the charge power information that CPLD/FPGA translation interface received power measuring circuit 1 transmits, after transport module 02 receives charge power information, can be with this charge power communication to ARM9 statistics and output circuit 04;
Mileage collection radio network gateway 03 gathers daily travel information, calculates expectation and the variance of daily travel by the daily travel information that gathers, and the daily travel expectation and the variance information output that calculate are added up and output circuit 04 to ARM9;
ARM9 statistics and output circuit 04 gather radio network gateway 03 with transport module 02 and mileage respectively and are connected, receive the power information of transport module 02 transmission, the daily travel that gathers radio network gateway 03 transmission with mileage is expected and variance information, by the expectation of described charge power information and described daily travel and variance information are added up, obtain local charging station expectation and the variance information constantly that begins to charge, the local charging station that obtains is begun to charge expectation constantly and variance communication to integrated system 2.
ARM9 statistics and output circuit 04 in integrated system 2 and local measurement and statistic unit 1 are connected, the local charging station that receives ARM9 statistics and output circuit 04 transmission begins expectation and the variance information constantly of charging, begin according to a plurality of local charging stations expectation and the variance yields constantly that charge, electrically-charging equipment areally-distributed data and electric automobile increase the charge power demand information that the scale data are calculated distribution zone corresponding to described a plurality of local charging stations, determine this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in this distribution zone, calculate the indices of the following Distribution Network Load Data curve in this zone, ratio according to the different charging modes of indices configuration electric automobile, calculate each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
The utility model embodiment provides charging electric vehicle facility proportional arrangement system has realized the automatic configuration of charging electric vehicle facility ratio by the synergy of local measurement and statistic unit and integrated system.
The structured flowchart of the integrated system that Fig. 2 provides for the utility model embodiment, as shown in Figure 2, integrated system is connected to form successively by five treatment facilities, be respectively the first treatment facility 201, the second treatment facility 202, the three treatment facilities 203, the are managed equipment 204 and the 5th treatment facility 205 everywhere;
Wherein, the first treatment facility 201 calculates the charge power demand information in distribution zone corresponding to described a plurality of local charging stations according to a plurality of local charging stations begin to charge expectation constantly and variance yields, electrically-charging equipment areally-distributed data and electric automobile growth scale;
The second treatment facility 202 is connected with described the first treatment facility 201, determines this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in described distribution zone;
The 3rd treatment facility 203 is connected with described the second treatment facility 202, calculates the 3rd treatment facility of the indices of this following Distribution Network Load Data curve in distribution zone;
Optionally, distribution zone following Distribution Network Load Data curve indices can be peak load increment index, peak load duration, peak load smoothing factor and average load smoothing factor.
The manages equipment 204 everywhere is connected with described the 3rd treatment facility 203, manages equipment everywhere according to the of the ratio of the different charging modes of indices configuration electric automobile;
The 5th treatment facility 205 and described is managed equipment 204 everywhere and is connected, and calculates the 5th treatment facility of each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
Optionally, above-mentioned treatment facility all can be the IPC-810 industrial control host, can be obviously also other the treatment facility that can carry out computing, as single-chip microcomputer etc.
Another structured flowchart of the integrated system that Fig. 3 provides for the utility model embodiment, as shown in Figure 3, integrated system 2 can comprise an integrated treatment facility 21, integrated treatment facility 21 comprises power demand predicting unit 211, Distribution Network Load Data curve prediction unit 212, index budget unit 213, charging modes proportional arrangement unit 214 and electrically-charging equipment proportional arrangement unit 215, wherein, index budget unit 213 can comprise again: the first computation subunit 2131, the second computation subunit 2132, the 3rd computation subunit 2133 and the 4th computation subunit 2134;
Wherein, described power demand predicting unit 211 obtains electrically-charging equipment areally-distributed data, electric automobile by the Ethernet transmission technology and increases that in scale data, distribution zone, each local charging station begins expectation and the variance yields constantly that charge, and then draws after treatment the charge power demand in whole distribution zone;
The Distribution Network Load Data curve of this following Distribution Network Load Data curve in distribution zone is determined according to the charge power demand information of power demand predicting unit 211 calculating in described power distribution network load curve forecasting unit 212;
The following Distribution Network Load Data curve in distribution zone that index budget unit 213 is determined according to power distribution network load curve forecasting unit 212 calculates the indices of this following Distribution Network Load Data curve in distribution zone.
Wherein, the first computation subunit 2131 can be calculated peak load increment index, the second computation subunit 2132 can be calculated the peak load duration, and the 3rd computation subunit 2133 can be calculated the peak load smoothing factor, and the 4th computation subunit 2134 can be calculated the average load smoothing factor.
Described charging modes proportional arrangement unit 214 can configure according to the indices of load curve the ratio of the different charging modes of electric automobile;
The ratio of the different charging modes of electric automobile that electrically-charging equipment proportional arrangement unit 215 can calculate according to charging modes proportional arrangement unit 214, and existing electrically-charging equipment capacity data calculates each regional electrically-charging equipment best configuration ratio of following distribution.
Fig. 2 and integrated system shown in Figure 3, the Different Effects of the different charge power demands that cause according to the different charging modes of electric automobile to the Distribution Network Load Data curve proposes four load curve indexs for assessment of the impact on the Distribution Network Load Data curve under the different proportion configuration of different charging modes electric automobiles.Then combined charge facility capacity data are carried out proportional arrangement to the construction of following electrically-charging equipment.This configuration-system is more accurate, efficient is better, and can carry out proportional arrangement according to the actual conditions of each different regions.Can show in real time data and memory function is arranged, facilitating data query and management; According to the moon statistics, year statistics, the further concrete configuration of statistical research charging electric vehicle facility ratio.
Optionally, ARM9 statistics and output circuit 04 can adopt the S3C2440A chip.
Optionally, power demand predicting unit 211 can receive by wireless data transmission technology the parameter of local charging station, thereby obtains the charge power demand in whole distribution zone.
Optionally, power distribution network load curve forecasting unit 212 can obtain the electrically-charging equipment areally-distributed data and electric automobile increases the scale data by the Ethernet transmission technology, thereby obtains required following Distribution Network Load Data curve.
Charging electric vehicle facility proportional arrangement method and system compared with prior art also has the following advantages:
1, voltage and current measurement module employing ATT7022C chip is the exemplary voltages electric current connected mode of the current/voltage three-phase power supply system of core, and its operational capability is powerful, certainty of measurement is high;
2, system adopts the full-embedded type method for designing, wherein assess software and adopt the Linux embedded real-time operating system of opening source code, measuring platform adopts ARM9 and DSP to form multi-CPU system, greatly improve the reliability of measure-controlling unit, had stronger reliability, network communications capability and expandability.
The structure chart of Fig. 4 provides for the utility model embodiment electric quantity acquisition unit, in the utility model embodiment, the electric quantity acquisition unit is the combination of power-measuring circuit and transport module, and as shown in Figure 4: collecting unit has preposition signal condition module, A/D acquisition module DSP processing module to consist of successively.The voltage to the collection point, the collection of current signal information are mainly completed in the electric quantity acquisition unit, and to the hard ware measure of frequency and the phase place of voltage, electric current.The input of electric quantity acquisition unit is directly from voltage, the electric current input variable of instrument transformer secondary side, signal is being input to the frequency acquisition dedicated input mouth of A/D acquisition module and DSP processing module by signal condition modules such as bandpass filterings (45-55HZ), at last carry out the computing of data by the DSP processing module, and data are sent to the dual port RAM transport module, be sent to ARM9 statistics and output unit by the dual port RAM transport module.In the utility model, this installs needs sampling 4 road voltage signals and 4 road current signals, samples simultaneously in order to satisfy 8 the road, adopts high speed 8 road or with upper channel A/D acquisition module, coordinates 8 road sampling holders to carry out the electric current and voltage sampling.
The ARM9 statistics that Fig. 5 provides for the utility model embodiment and the structure chart of output circuit, as shown in the figure: consist of statistics and output unit by the ARM9 processor, ARM9 and DSP processing module directly utilize the dual port RAM transport module to carry out the transmission of data.Its utilize dual port RAM and DSP carry out data transmission, read and unified management, complete data communication facility by Ethernet, data, CRC check code and the temporal information measured are packaged into Frame, through Ethernet, data are sent to host computer and carry out web displaying.ARM9 statistics and output unit also comprise 2, RS485/232 interface, 1 of Ethernet interface, usb 1, CF card or one, electronic hard disc interface, one, LCD interface, and this plate carries the functional circuits such as RTC.
The flow chart of a kind of charging electric vehicle facility proportional arrangement method that Fig. 6 provides for the utility model embodiment, as shown in Figure 6, the method can comprise step:
Step 601, local measurement and statistic unit gather local Vehicular charging power information, and daily travel information;
Step 602, local measurement and statistic unit are with described charge power information and described daily travel is expected and variance information is added up, and obtain local charging station and begin expectation and the variance information constantly of charging;
Step 603, the integrated system that is connected with described local measurement and statistic unit increase according to a plurality of local charging stations begin to charge expectation constantly and variance yields, electrically-charging equipment areally-distributed data and electric automobile the charge power demand information that the scale data are calculated distribution zone corresponding to described a plurality of local charging stations;
Step 605, described integrated system configure the ratio of the different charging modes of electric automobile according to indices, calculate each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
Fig. 7 is the flow chart of the prediction of electric automobile power demand, Distribution Network Load Data curve prediction and index calculating method, and as shown in the figure, flow chart is as follows:
1. select the input data that can reflect the electric power demand characteristics, the electric automobile recoverable amount, the electric automobile that comprise charging modes, the distribution zone of purposes, the electric automobile of electric automobile increase scale, the electrically-charging equipment areally-distributed data, charging electric vehicle power data and probabilistic model.
2. at first judge the function type of electric automobile, thereby obtain corresponding distance travelled probabilistic model characteristic parameter; Then the initial SOC of storage battery is sampled and determine accordingly charging interval length by the SOC calculating formula; Obtain beginning charging probabilistic model and to its sampling constantly in conjunction with concrete vehicle again; At last according to begin to charge constantly, the sample value of initial SOC and corresponding charging interval length thereof determines the charge power of separate unit electric automobile.The daily travel d of electric automobile satisfies logarithm normal distribution,
(1)
Wherein, μ and σ 2 are respectively logarithm average and variance.Suppose that electric automobile all just begins to travel after storage battery is full of, the initial state-of-charge SOC of storage battery is suc as formula (2), and its probability density function fSOC (x) is relevant to stochastic variable d simultaneously, under different initial SOC, charge in batteries is as follows to the required charging interval length T c of Full Charge Capacity
T
c=g
-1(SOC),
Wherein, α is the interval number of days of adjacent twice charging; D is the electric automobile daily travel; DR is the maximum range of electric automobile; Tcmax is SOC from 0% to 100% required time; P (t) is the electric vehicle charging electrical power.
3. the beginning to charge and constantly depend on the function type of himself of electric automobile, distribute if it satisfies evenly, can extract according to its probability-distribution function.
4. when the electric automobile permeability fixedly the time, can adopt by adjusting the ratio beta of quick charge mode electric automobile, charging behavior and the Distribution Network Load Data curve of electric automobile are complementary, and the paddy effect of filling out of performance charging load, reduce the load impact to distribution simultaneously more fully.Be the impact of charging electric vehicle access on the distribution peak load under the quantitative analysis different proportion, definition peak load increment index η LM and peak load duration index TLM are as follows,
In formula, P0Lmax is the original loads peak value, and PL (t) and PnLmax are respectively sequential load and the new load peak after electric automobile access distribution, and μ is the load level parameter (μ=85%) of appointment, and T is load curve cycle (T=24h).Consider the impact that the electric automobile behavior of charging is at random fluctuateed on Distribution Network Load Data, definition peak load smoothing factor η LSmax and average load smoothing factor η LSavg are as follows,
In formula, PLavg is the average load in time 0～Δ T, and Δ T is the time interval (Δ T=2h), n=1, and 2 ..., N and N=T/ Δ T.
Because η LM, TLM, η LSmax and η LSavg are more little more excellent type index, four index linear weighted functions can be got overall target η LC=[ω M, ω TM, ω Smax, ω Savg] [η LM, TLM, η LSmax, η LSavg] T, and select the ratio beta of Quick charging electric automobile as target take η LC minimum.Then according to the electrically-charging equipment of the capacity data geometric ratio configuration same ratio of the proportional arrangement combined charge facility of charging modes.
To the above-mentioned explanation of the disclosed embodiments, make this area professional and technical personnel can realize or use the utility model.Multiple modification to these embodiment will be apparent concerning those skilled in the art, and General Principle as defined herein can be in the situation that do not break away from spirit or scope of the present utility model, realization in other embodiments.Therefore, the utility model will can not be restricted to these embodiment shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (6)
1. a charging electric vehicle facility proportional arrangement system, is characterized in that, this system comprises: local measurement and statistic unit, and described local measurement and statistic unit comprise:
Gather local Vehicular charging power information, and with the power-measuring circuit of this power information output;
Be connected with described power-measuring circuit, receive described power information, and export the transport module of described power information;
Gather daily travel information, calculate daily travel expectation and variance, and the output daily travel expectation of calculating and the mileage collection radio network gateway of variance information;
Gathering radio network gateway with described transport module and described mileage respectively is connected, receive described power information, and described daily travel expectation and variance information, by the expectation of described charge power information and described daily travel and variance information are added up, obtain local charging station and begin expectation and the variance information constantly of charging, and export described begin the to charge expectation in the moment and ARM9 statistics and the output circuit of variance information;
be connected with described ARM9 statistics and output circuit, receive described expectation and the variance information constantly of charging that begins, begin according to a plurality of local charging stations expectation and the variance yields constantly that charge, electrically-charging equipment areally-distributed data and electric automobile increase the charge power demand information that the scale data are calculated distribution zone corresponding to described a plurality of local charging stations, determine this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in this distribution zone, calculate the indices of the following Distribution Network Load Data curve in this zone, ratio according to the different charging modes of indices configuration electric automobile, calculate the integrated system of each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
2. system according to claim 1, is characterized in that, described integrated system comprises:
Increase according to a plurality of local charging stations begin to charge expectation constantly and variance yields, electrically-charging equipment areally-distributed data and electric automobile the first treatment facility that the scale data are calculated the charge power demand information in distribution zone corresponding to described a plurality of local charging stations;
Be connected with described the first treatment facility, determine the second treatment facility of this following Distribution Network Load Data curve in distribution zone according to the charge power demand information in described distribution zone;
Be connected with described the second treatment facility, calculate the 3rd treatment facility of the indices of this following Distribution Network Load Data curve in distribution zone;
Be connected with described the 3rd treatment facility, manage equipment everywhere according to the of the ratio of the different charging modes of indices configuration electric automobile;
With described everywhere reason equipment be connected, calculate the 5th treatment facility of each regional electrically-charging equipment best configuration ratio of following distribution according to this ratio and existing electrically-charging equipment capacity data.
3. system according to claim 1, is characterized in that, described transport module unit comprises: Double Port Random Memory RAM, and complex programmable logic device (CPLD)/Field Programmable Gate Array FPGA translation interface.
4. system according to claim 1, is characterized in that, described ARM9 statistics and output circuit are the S3C2440A chip.
5. system according to claim 1, is characterized in that, described power-measuring circuit, transport module, mileage gather between radio network gateway and ARM9 statistics and output circuit and adopt the Ethernet transmission technology to communicate.
6. system according to claim 2, is characterized in that, the included treatment facility of described integrated system is IPC-810 industrial computer host-processor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103701176A (en) * | 2014-01-02 | 2014-04-02 | 华北电力大学 | Method for computing allocation ratio of electric vehicle fast/slow charging facilities |
| CN103855739A (en) * | 2012-11-30 | 2014-06-11 | 余杭供电局 | Electric car charging facility proportional allocation system and method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103855739A (en) * | 2012-11-30 | 2014-06-11 | 余杭供电局 | Electric car charging facility proportional allocation system and method |
| CN103855739B (en) * | 2012-11-30 | 2016-02-17 | 国家电网公司 | Charging electric vehicle facility proportional arrangement system and method |
| CN103701176A (en) * | 2014-01-02 | 2014-04-02 | 华北电力大学 | Method for computing allocation ratio of electric vehicle fast/slow charging facilities |
| CN103701176B (en) * | 2014-01-02 | 2015-08-26 | 华北电力大学 | A kind of electric automobile soon, the computational methods of electrically-charging equipment allocation ratio at a slow speed |
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Owner name: STATE GRID CORPORATION OF CHINA Free format text: FORMER OWNER: STATE GRID ZHEJIANG HANGZHOU YUHANG DISTRICT POWER SUPPLY COMPANY Effective date: 20140422 Owner name: STATE GRID ZHEJIANG HANGZHOU YUHANG DISTRICT POWER Free format text: FORMER OWNER: STATE GRID CORPORATION OF CHINA Effective date: 20140422 |
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Owner name: STATE GRID ZHEJIANG HANGZHOU YUHANG DISTRICT POWER Free format text: FORMER NAME: YUHANG POWER SUPPLY BUREAU |
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Free format text: CORRECT: ADDRESS; FROM: 311100 HANGZHOU, ZHEJIANG PROVINCE TO: 100031 XICHENG, BEIJING |
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Address after: Linping Yuhang town Henan District Hangzhou city Zhejiang province 311100 Dai Patentee after: STATE GRID ZHEJIANG HANGZHOU YUHANG POWER SUPPLY Co. Patentee after: State Grid Corporation of China Address before: Linping Yuhang town Henan District Hangzhou city Zhejiang province 311100 Dai Patentee before: Yuhang Power Supply Bureau Patentee before: State Grid Corporation of China |
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Effective date of registration: 20140422 Address after: 100031 Xicheng District West Chang'an Avenue, No. 86, Beijing Patentee after: State Grid Corporation of China Patentee after: STATE GRID ZHEJIANG HANGZHOU YUHANG POWER SUPPLY Co. Patentee after: HANGZHOU POWER SUPPLY COMPANY OF STATE GRID ZHEJIANG ELECTRIC POWER Co. Patentee after: STATE GRID ZHEJIANG ELECTRIC POWER Co. Address before: Linping Yuhang town Henan District Hangzhou city Zhejiang province 311100 Dai Patentee before: STATE GRID ZHEJIANG HANGZHOU YUHANG POWER SUPPLY Co. Patentee before: State Grid Corporation of China |
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Granted publication date: 20130619 |
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