CN102593902A - Energy-equivalence-based load forecasting system and method for electric automobile charging facility - Google Patents

Abstract

The invention discloses an energy-equivalence-based load forecasting system and method for an electric automobile charging facility, belonging to the technical field of planning and designing of an electric automobile. The system comprises an input module, a processing module and an output module; the input module is used for inputting initial data for forecasting the load of the electric automobile charging facility; the processing module is used for computing the maximum load of a regional charging facility and the maximum load of a centralized charging facility; and the output module is used for displaying and outputting the maximum load of the regional charging facility and the maximum load of the centralized charging facility. The method comprises the following steps of: inputting the initial data for forecasting the load of the electric automobile charging facility; computing the maximum load of the regional charging facility and the maximum load of the centralized charging facility according to input data; and outputting the maximum load of the regional charging facility and the maximum load of the centralized charging facility. According to the invention, the charging load of the regional electric automobile can be exactly forecast.

Description

Charging electric vehicle load of utility prognoses system and method based on the energy equivalence

Technical field

The invention belongs to electric automobile planning and designing technical field, relate in particular to a kind of charging electric vehicle load of utility prognoses system and method based on the energy equivalence.

Background technology

Along with the development of electric automobile, the construction of charging electric vehicle infrastructure must pick up the pace, even needs planning in advance, in order to make planning rationally, accurately, avoids blindness, need predicting the charging electric vehicle load.

Summary of the invention

The objective of the invention is to, propose a kind of charging electric vehicle load prediction system and Forecasting Methodology thereof based on the energy equivalence.

For realizing above-mentioned purpose; Technical scheme provided by the invention is; A kind of charging electric vehicle load of utility prognoses system based on the energy equivalence; It is characterized in that said prognoses system comprises: input module, processing module and output module, said processing module link to each other with output module with input module respectively;

Said input module is used to import the initial data of prediction charging electric vehicle load of utility, and the data of input are sent to processing module;

Wherein, the initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The said reference data that influences the factor of electrically-charging equipment load prediction comprises maximum use hourage in benchmark permeability, benchmark dispersion rate, reference area maximum use hourage and the benchmark set;

The said achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights;

Said gas station data comprise that each gas station is to the distance of each electrically-charging equipment, the expection sales volume that each gas station arrives each regional distance and each gas station;

Said car data comprises per ton hundred kilometers power consumptions and the fuel consumption per hundred kilometers of orthodox car of weight, the electric automobile of electric automobile;

Said processing module comprises regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, permeability computing unit, concentration ratio computing unit, concentrates charge volume apportionment ratio computing unit, concentrated maximum use hourage computing unit, regional electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load calculating unit;

Wherein, regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit and permeability computing unit link to each other with regional electrically-charging equipment peak load calculating unit respectively;

Permeability computing unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit calculate the unit with concentrated electrically-charging equipment peak load respectively with concentrated maximum use hourage computing unit and link to each other;

Said regional maximum use hourage computing unit is used for according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage, and regional maximum use hourage is sent to regional electrically-charging equipment peak load calculating unit;

Said dispersion rate computing unit is used for calculating dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and dispersion rate is sent to regional electrically-charging equipment peak load calculating unit;

Said dispersion charge volume apportionment ratio computing unit is used for disperseing the charge volume apportionment ratio according to each gas station to each regional distance and each regional population's scale data computation, and will disperse the charge volume apportionment ratio to send to regional electrically-charging equipment peak load and calculate the unit;

Said permeability computing unit is used for calculating permeability according to benchmark permeability, permeability desired value and permeability weights; Calculate gas station's equivalence charge volume, and gas station's equivalence charge volume is sent to regional electrically-charging equipment peak load calculating unit and concentrated electrically-charging equipment peak load calculating unit respectively according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car;

Said concentration ratio computing unit is used for calculating concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and concentration ratio is sent to concentrated electrically-charging equipment peak load calculating unit;

Said concentrated charge volume apportionment ratio computing unit is used for concentrating the charge volume apportionment ratio according to each gas station to the distance calculation of each electrically-charging equipment, and will concentrate the charge volume apportionment ratio to send to and concentrate the electrically-charging equipment peak load to calculate the unit;

Said concentrated maximum use hourage computing unit is used for according to benchmark set maximum use hourage, concentrates maximum use hourage in maximum use hourage desired value and the concentrated maximum use hourage weights calculated set, and will concentrate the maximum use hourage to send to and concentrate the electrically-charging equipment peak load to calculate the unit;

Said regional electrically-charging equipment peak load is calculated the unit and is used for the charging amount of bearing according to dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment; Send to output module again according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment, and with regional electrically-charging equipment peak load;

Said concentrated electrically-charging equipment peak load is calculated the unit and is used for the charging demand according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume calculated set electrically-charging equipment; Again according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set, and will concentrate the electrically-charging equipment peak load to send to output module;

Said output module is used for viewing area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load, and is used for printout zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

A kind of charging electric vehicle load of utility Forecasting Methodology based on the energy equivalence is characterized in that said method comprises:

Step 1: the initial data of input prediction charging electric vehicle load of utility; Wherein, the initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The said reference data that influences the factor of electrically-charging equipment load prediction comprises maximum use hourage in benchmark permeability, benchmark dispersion rate, reference area maximum use hourage and the benchmark set;

The said achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights;

Said gas station data comprise that each gas station is to the distance of each electrically-charging equipment, the expection sales volume that each gas station arrives each regional distance and each gas station;

Said car data comprises per ton hundred kilometers power consumptions and the fuel consumption per hundred kilometers of orthodox car of weight, the electric automobile of electric automobile;

Step 2: data computation zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load according to input specifically comprise:

Step 201: according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage;

Calculate dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights;

Disperse the charge volume apportionment ratio according to each gas station to each regional distance and each regional population's scale data computation;

Calculate permeability according to benchmark permeability, permeability desired value and permeability weights;

Calculate concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights;

Concentrate the charge volume apportionment ratio according to each gas station to the distance calculation of each electrically-charging equipment;

According to maximum use hourage in maximum use hourage, concentrated maximum use hourage desired value and the concentrated maximum use hourage weights calculated set in the benchmark set;

Step 202: calculate gas station's equivalence charge volume, execution in step 203 and step 205 respectively according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car;

Step 203: according to the charging amount of bearing of dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment;

Step 204:: according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment, execution in step 207;

Step 205: according to the charging demand of electrically-charging equipment in concentration ratio, concentrated charge volume apportionment ratio and the gas station's equivalence charge volume calculated set;

Step 206: according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set, execution in step 207;

Step 207: sending zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load;

Step 3: output area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

The present invention is the load of estimation range charging electric vehicle facility exactly, for research charging electric vehicle load of utility provides the basis to the influence of electrical network, also for the charging electric vehicle facilities planning foundation is provided.

Description of drawings

Fig. 1 is based on the charging electric vehicle load of utility prognoses system structure chart of energy equivalence;

Fig. 2 is based on the charging electric vehicle load of utility Forecasting Methodology flow chart of energy equivalence;

Fig. 3 is the weight table of achievement data that influences the factor of electrically-charging equipment load prediction;

Fig. 4 is that the equivalence of a certain gas station distributes sketch map for the equivalent charge volume of concentrating electrically-charging equipment;

Fig. 5 is that the equivalence of a certain gas station distributes sketch map for the charging amount of bearing of regional electrically-charging equipment.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that following explanation only is exemplary, rather than in order to limit scope of the present invention and application thereof.

Fig. 1 is based on the charging electric vehicle load of utility prognoses system structure chart of energy equivalence.Among Fig. 1, the charging electric vehicle load of utility prognoses system based on the energy equivalence provided by the invention comprises: input module, processing module and output module.Wherein, processing module links to each other with output module with input module respectively.

Input module is used to import the initial data of prediction charging electric vehicle load of utility, and the data of input are sent to processing module.

The initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data.

In the present embodiment, choose the factor that influences the electrically-charging equipment load prediction and comprise economy/income level, area type, scale and position; The electric automobile price; Go/continual mileage vehicle laws of use/orderly management, charging price; The electrically-charging equipment system, quality and totally 9 kinds of maintenance and other policy factors.To the factor that influences the electrically-charging equipment load prediction, confirm reference data, desired value and weights.

The reference data that influences the factor of electrically-charging equipment load prediction comprises maximum use hourage in benchmark permeability, benchmark dispersion rate, reference area maximum use hourage and the benchmark set.

The achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights.

Gas station's data comprise that each gas station is to the distance of each electrically-charging equipment, the expection sales volume that each gas station arrives each regional distance and each gas station.

Car data comprises per ton hundred kilometers power consumptions and the fuel consumption per hundred kilometers of orthodox car of weight, the electric automobile of electric automobile.

Processing module comprises regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, permeability computing unit, concentration ratio computing unit, concentrates charge volume apportionment ratio computing unit, concentrated maximum use hourage computing unit, regional electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load calculating unit.Wherein, regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit and permeability computing unit link to each other with regional electrically-charging equipment peak load calculating unit respectively.Permeability computing unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit calculate the unit with concentrated electrically-charging equipment peak load respectively with concentrated maximum use hourage computing unit and link to each other.

Zone maximum use hourage computing unit is used for according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage, and regional maximum use hourage is sent to regional electrically-charging equipment peak load calculating unit.

The dispersion rate computing unit is used for calculating dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and dispersion rate is sent to regional electrically-charging equipment peak load calculating unit.

Disperse charge volume apportionment ratio computing unit to be used for disperseing the charge volume apportionment ratio to each regional distance and each regional population's scale data computation, and will disperse the charge volume apportionment ratio to send to regional electrically-charging equipment peak load and calculate the unit according to each gas station.

The permeability computing unit is used for calculating permeability according to benchmark permeability, permeability desired value and permeability weights; Calculate gas station's equivalence charge volume, and gas station's equivalence charge volume is sent to regional electrically-charging equipment peak load calculating unit and concentrated electrically-charging equipment peak load calculating unit respectively according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car.

The concentration ratio computing unit is used for calculating concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and concentration ratio is sent to concentrated electrically-charging equipment peak load calculating unit.

Concentrate charge volume apportionment ratio computing unit to be used for concentrating the charge volume apportionment ratio to the distance calculation of each electrically-charging equipment, and will concentrate the charge volume apportionment ratio to send to and concentrate the electrically-charging equipment peak load to calculate the unit according to each gas station.

Concentrate maximum use hourage computing unit to be used for according to benchmark set maximum use hourage, to concentrate maximum use hourage in maximum use hourage desired value and the concentrated maximum use hourage weights calculated set, and will concentrate the maximum use hourage to send to and concentrate the electrically-charging equipment peak load to calculate the unit.

Zone electrically-charging equipment peak load is calculated the unit and is used for the charging amount of bearing according to dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment; Send to output module again according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment, and with regional electrically-charging equipment peak load.

Concentrate the electrically-charging equipment peak load to calculate the unit and be used for charging demand according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume calculated set electrically-charging equipment; Again according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set, and will concentrate the electrically-charging equipment peak load to send to output module.

Output module is used for viewing area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load, and is used for printout zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.Output module also is used for demonstrating all types of zones (shopping centre, office building, residential area) and charging station with the form of element; Click certain element and can eject a display window; Show that computing module is to the result of calculation of this element and the partial data of the original input of element (sign, coordinate, type, scale); Through dragging each element, can put their relative position.In addition, output module can also print the plane graph that comprises each element, also can generate the electronic document that contains each component information (sign, coordinate, type, scale, peak load etc.).

Fig. 2 is based on the charging electric vehicle load of utility Forecasting Methodology flow chart of energy equivalence.Among Fig. 2, the charging electric vehicle load of utility Forecasting Methodology based on the energy equivalence provided by the invention comprises:

Step 1: the initial data of input prediction charging electric vehicle load of utility.Wherein, the initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data.

The reference data that influences the factor of electrically-charging equipment load prediction comprises benchmark permeability α _F0, benchmark dispersion rate β _F0, reference area maximum use hourage σ _D0With maximum use hourage σ in the benchmark set _C0

The achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights.Fig. 3 is the weight table of achievement data that influences the factor of electrically-charging equipment load prediction.Provided the concrete numerical value of permeability weights, dispersion rate weights, regional maximum use hourage weights and concentrated maximum use hourage weights among Fig. 3.And the permeability desired value in the present embodiment, dispersion rate desired value, regional maximum use hourage desired value and concentrated maximum use hourage desired value (are the x among Fig. 3 ₁-x ₉) can rule of thumb draw or utilize least square fitting to draw.

Gas station's data comprise each gas station to each electrically-charging equipment apart from r _FC(ki), promptly k gas station to the distance of i electrically-charging equipment; Each gas station to each the zone apart from r _FD(kj), promptly k gas station to the distance in j zone; The expection sales volume F (k) of each gas station.

Car data comprises the fuel consumption per hundred kilometers M (get in the present embodiment M=8 liter/hundred kilometer) of the weight H (getting the H=2 ton in the present embodiment) of electric automobile, per ton hundred kilometers power consumption p of electric automobile (getting p=10 kilowatt-hour/ton hundred kilometers in the present embodiment) and orthodox car.

Each regional population's scale data is just got this regional population total amount.

Step 2: data computation zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load according to input specifically comprise:

Step 201: according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage.Its computing formula is:

${\mathrm{\σ}}_D\left(j\right)={\mathrm{\σ}}_{D0}\underset{i=1}{\overset{9}{\mathrm{\Σ}}}{g}_i{x}_{\mathrm{ji}}---\left(1\right)$

Wherein, σ _D(j) be the regional maximum use hourage in j zone, σ _D0Be reference area maximum use hourage, g _i(i=1,2 ..., 9) be that under the regional maximum use hourage each influences the weights of the factor of electrically-charging equipment load prediction, x _JiBe j the zone each influence the desired value of the factor of electrically-charging equipment load prediction.

Calculate dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights; Its computing formula is:

${\mathrm{\β}}_F\left(j\right)={\mathrm{\β}}_{F0}\underset{i=1}{\overset{9}{\mathrm{\Σ}}}{f}_i{x}_{\mathrm{ji}}---\left(2\right)$

Wherein, β _F(j) be the dispersion rate in j zone, β _F0Be benchmark dispersion rate, f _i(i=1,2 ..., 9) influence the weights of the factor of electrically-charging equipment load prediction, x under the dispersion rate each _JiBe j the zone each influence the desired value of the factor of electrically-charging equipment load prediction.

Disperse the charge volume apportionment ratio according to each gas station to each regional distance and each regional population's scale data computation.Because need disperse charge capacity to be assigned near the zone the k of gas station this, charge capacity then will not be distributed in the zone that exceeds certain distance.As shown in Figure 4; For this distance with interior zone; Here employing waits load apart from apportion design, owing to be to be assigned to the zone to equivalent electric quantity from the gas station, therefore also need consider the population size of zones of different except the distance between consideration gas station and the zone here; Be that apportionment ratio is directly proportional with regional population's scale, be inversely proportional to distance.Therefore, the computing formula of dispersion charge volume apportionment ratio that is assigned to j zone from k gas station is:

${\mathrm{\λ}}_{\mathrm{FD}}\left(\mathrm{kj}\right)=\left\{\begin{array}{cc}\frac{n_j/r_{\mathrm{FD}}\left(\mathrm{kj}\right)}{\underset{l=1}{\overset{J}{\mathrm{\Σ}}}{n}_l/r_{\mathrm{FD}}\left(\mathrm{kl}\right)},& r_{\mathrm{FD}}\left(\mathrm{kj}\right)\≤r_{\mathrm{FD}\max }\\ 0,& r_{\mathrm{FD}}\left(\mathrm{kj}\right)>r_{\mathrm{FD}\max }\end{array}\right.---\left(3\right)$

Wherein, λ _FD(kj) be the dispersion charge volume apportionment ratio that k gas station is assigned to j zone, r _FD(kj) be the distance of k gas station to j zone, J is the regional number in the setpoint distance, r _FDmaxBe setpoint distance, charge capacity will not be distributed in the zone that exceeds this distance.

Calculate permeability according to benchmark permeability, permeability desired value and permeability weights.Its computing formula is:

${\mathrm{\α}}_F\left(j\right)={\mathrm{\α}}_{F0}\underset{i=1}{\overset{9}{\mathrm{\Σ}}}{e}_i{x}_{\mathrm{ji}}---\left(4\right)$

Wherein, α _F(j) be the permeability in j zone, α _F0Be benchmark permeability, e _i(i=1,2 ..., 9) be that under the permeability each influences the weights of the factor of electrically-charging equipment load prediction, x _JiBe j the zone each influence the desired value of the factor of electrically-charging equipment load prediction.

Calculate concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights.Its computing formula is:

${\mathrm{\γ}}_F\left(j\right)=1-{\mathrm{\β}}_F\left(j\right)=1-{\mathrm{\β}}_{F0}\underset{i=1}{\overset{9}{\mathrm{\Σ}}}{f}_i{x}_{\mathrm{ji}}---\left(5\right)$

Wherein, β _F(j) be the dispersion rate in j zone, β _F0Be benchmark dispersion rate, f _i(i=1,2 ..., 9) influence the weights of the factor of electrically-charging equipment load prediction, x under the dispersion rate each _JiBe j the zone each influence the desired value of the factor of electrically-charging equipment load prediction.

Concentrate the charge volume apportionment ratio according to each gas station to the distance calculation of each electrically-charging equipment.Owing to need this concentrated charge capacity be assigned near the concentrated electrically-charging equipment the k of gas station; The concentrated electrically-charging equipment that exceeds certain distance then will not distribute charge capacity; As shown in Figure 5,, still adopt here and wait load with interior concentrated electrically-charging equipment for this distance apart from apportion design.Therefore, the computing formula that is assigned to the concentrated charge volume apportionment ratio of i concentrated electrically-charging equipment from k gas station is:

${\mathrm{\λ}}_{\mathrm{FC}}\left(\mathrm{ki}\right)=\left\{\begin{array}{cc}\frac{1/r_{\mathrm{FC}}\left(\mathrm{ki}\right)}{\underset{l=1}{\overset{I}{\mathrm{\Σ}}}1/r_{\mathrm{FC}}\left(\mathrm{kl}\right)},& r_{\mathrm{FC}}\left(\mathrm{ki}\right)\≤r_{\mathrm{FD}\max }\\ 0,& r_{\mathrm{FC}}\left(\mathrm{ki}\right)>r_{\mathrm{FD}\max }\end{array}\right.---\left(6\right)$

Wherein, λ _FC(ki) be the concentrated charge volume apportionment ratio that k gas station is assigned to i concentrated electrically-charging equipment, r _FC(ki) be the distance of k gas station to i concentrated electrically-charging equipment, I is the concentrated electrically-charging equipment number in the setpoint distance, r _FCmaxBe setpoint distance, the concentrated electrically-charging equipment that exceeds this distance will not distribute charge capacity.

According to maximum use hourage in maximum use hourage, concentrated maximum use hourage desired value and the concentrated maximum use hourage weights calculated set in the benchmark set.Its computing formula is:

${\mathrm{\σ}}_C\left(j\right)={\mathrm{\σ}}_{C0}\underset{i=1}{\overset{9}{\mathrm{\Σ}}}{h}_i{x}_{\mathrm{ji}}---\left(7\right)$

Wherein, σ _C(j) be the concentrated maximum use hourage of j concentrated electrically-charging equipment, σ _C0Be maximum use hourage in the benchmark set, h _i(i=1,2 ..., 9) influence the weights of the factor of electrically-charging equipment load prediction, x for concentrating under the maximum use hourage each _JiBe j electrically-charging equipment each influence the desired value of the factor of electrically-charging equipment load prediction.

Step 202: calculate gas station's equivalence charge volume according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car.Its computing formula is:

$E_F\left(k\right)=\frac{{\mathrm{\α}}_F\left(k\right)\×s\×p\×H\×F\left(k\right)}{M}---\left(8\right)$

Wherein, E _F(k) be the equivalent charge volume of k gas station, α _F(k) be the permeability of k gas station, s is oil product unit conversion coefficient (present embodiment equals 1378 liters of calculating by gasoline per ton), and H is the weight of electric automobile, and p is per ton hundred kilometers power consumptions of electric automobile, and M is the fuel consumption per hundred kilometers per ton of electric automobile.

After calculating gas station's equivalence charge volume, difference execution in step 203 and step 205.

Step 203: according to the charging amount of bearing of dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment.Its computing formula is:

$E_D\left(j\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\λ}}_{\mathrm{FD}}\left(\mathrm{kj}\right){\mathrm{\β}}_F\left(k\right)E_F\left(k\right)---\left(9\right)$

Wherein, E _D(j) be the charging amount of bearing of the regional electrically-charging equipment in j zone, λ _FD(kj) be the dispersion charge volume apportionment ratio that k gas station is assigned to j zone, β _F(k) be dispersion rate, E _F(k) be the equivalent charge volume of k gas station, K is gas station's number.

Step 204:: according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment.Its computing formula is:

P _Dmax(j)＝E _D(j)/σ _D(j) (10)

Wherein, P _Dmax(j) be the regional electrically-charging equipment peak load in j zone, E _D(j) be the charging amount of bearing of the regional electrically-charging equipment in j zone, σ _D(j) be the regional maximum use hourage in j zone.

After obtaining the regional maximum use hourage in each zone, execution in step 207.

Step 205: according to the charging demand of electrically-charging equipment in concentration ratio, concentrated charge volume apportionment ratio and the gas station's equivalence charge volume calculated set.Its computing formula is:

$E_C\left(i\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\λ}}_{\mathrm{FC}}\left(\mathrm{ki}\right){\mathrm{\γ}}_F\left(k\right)E_F\left(k\right)---\left(11\right)$

Wherein, E _C(i) be the charging demand of i concentrated electrically-charging equipment, λ _FC(ki) for be assigned to the concentrated charge volume apportionment ratio of i concentrated electrically-charging equipment, E from k gas station _F(k) be the equivalent charge volume of k gas station, γ _F(k) be concentration ratio, K is gas station's number.

Step 206: according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set.Its computing formula is:

P _Cmax(i)＝E _C(i)/σ _C(i) (12)

Wherein, P _Cmax(i) be i concentrated electrically-charging equipment peak load, E _C(i) be the charging demand of i concentrated electrically-charging equipment, σ _C(i) be the concentrated maximum use hourage of i concentrated electrically-charging equipment.

After obtaining the concentrated electrically-charging equipment peak load of each concentrated electrically-charging equipment, execution in step 207.

Step 207: sending zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

Step 3: output area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

The above; Be merely the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, any technical staff who is familiar with the present technique field is in the technical scope that the present invention discloses; The variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (2)

1. charging electric vehicle load of utility prognoses system based on energy equivalence, it is characterized in that said prognoses system comprises: input module, processing module and output module, said processing module link to each other with output module with input module respectively;

Said input module is used to import the initial data of prediction charging electric vehicle load of utility, and the data of input are sent to processing module;

Wherein, the initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The said reference data that influences the factor of electrically-charging equipment load prediction comprises maximum use hourage in benchmark permeability, benchmark dispersion rate, reference area maximum use hourage and the benchmark set;

The said achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights;

Said gas station data comprise that each gas station is to the distance of each electrically-charging equipment, the expection sales volume that each gas station arrives each regional distance and each gas station;

Said car data comprises per ton hundred kilometers power consumptions and the fuel consumption per hundred kilometers of orthodox car of weight, the electric automobile of electric automobile;

Said processing module comprises regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, permeability computing unit, concentration ratio computing unit, concentrates charge volume apportionment ratio computing unit, concentrated maximum use hourage computing unit, regional electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load calculating unit;

Wherein, regional maximum use hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit and permeability computing unit link to each other with regional electrically-charging equipment peak load calculating unit respectively;

Permeability computing unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit calculate the unit with concentrated electrically-charging equipment peak load respectively with concentrated maximum use hourage computing unit and link to each other;

Said regional maximum use hourage computing unit is used for according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage, and regional maximum use hourage is sent to regional electrically-charging equipment peak load calculating unit;

Said dispersion rate computing unit is used for calculating dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and dispersion rate is sent to regional electrically-charging equipment peak load calculating unit;

Said dispersion charge volume apportionment ratio computing unit is used for disperseing the charge volume apportionment ratio according to each gas station to each regional distance and each regional population's scale data computation, and will disperse the charge volume apportionment ratio to send to regional electrically-charging equipment peak load and calculate the unit;

Said permeability computing unit is used for calculating permeability according to benchmark permeability, permeability desired value and permeability weights; Calculate gas station's equivalence charge volume, and gas station's equivalence charge volume is sent to regional electrically-charging equipment peak load calculating unit and concentrated electrically-charging equipment peak load calculating unit respectively according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car;

Said concentration ratio computing unit is used for calculating concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, and concentration ratio is sent to concentrated electrically-charging equipment peak load calculating unit;

Said concentrated charge volume apportionment ratio computing unit is used for concentrating the charge volume apportionment ratio according to each gas station to the distance calculation of each electrically-charging equipment, and will concentrate the charge volume apportionment ratio to send to and concentrate the electrically-charging equipment peak load to calculate the unit;

Said concentrated maximum use hourage computing unit is used for according to benchmark set maximum use hourage, concentrates maximum use hourage in maximum use hourage desired value and the concentrated maximum use hourage weights calculated set, and will concentrate the maximum use hourage to send to and concentrate the electrically-charging equipment peak load to calculate the unit;

Said regional electrically-charging equipment peak load is calculated the unit and is used for the charging amount of bearing according to dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment; Send to output module again according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment, and with regional electrically-charging equipment peak load;

Said concentrated electrically-charging equipment peak load is calculated the unit and is used for the charging demand according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume calculated set electrically-charging equipment; Again according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set, and will concentrate the electrically-charging equipment peak load to send to output module;

Said output module is used for viewing area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load, and is used for printout zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

2. charging electric vehicle load of utility Forecasting Methodology based on energy equivalence is characterized in that said method comprises:

Step 1: the initial data of input prediction charging electric vehicle load of utility; Wherein, the initial data of prediction charging electric vehicle load of utility comprises the reference data of the factor that influences the electrically-charging equipment load prediction, the achievement data that influences the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The said reference data that influences the factor of electrically-charging equipment load prediction comprises maximum use hourage in benchmark permeability, benchmark dispersion rate, reference area maximum use hourage and the benchmark set;

The said achievement data that influences the factor of electrically-charging equipment load prediction comprises permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, regional maximum use hourage desired value, regional maximum use hourage weights, concentrates maximum use hourage desired value and concentrated maximum use hourage weights;

Said gas station data comprise that each gas station is to the distance of each electrically-charging equipment, the expection sales volume that each gas station arrives each regional distance and each gas station;

Said car data comprises per ton hundred kilometers power consumptions and the fuel consumption per hundred kilometers of orthodox car of weight, the electric automobile of electric automobile;

Step 2: data computation zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load according to input specifically comprise:

Step 201: according to reference area maximum use hourage, regional maximum use hourage desired value and regional maximum use hourage weights zoning maximum use hourage;

Calculate dispersion rate according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights;

Disperse the charge volume apportionment ratio according to each gas station to each regional distance and each regional population's scale data computation;

Calculate permeability according to benchmark permeability, permeability desired value and permeability weights;

Calculate concentration ratio according to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights;

Concentrate the charge volume apportionment ratio according to each gas station to the distance calculation of each electrically-charging equipment;

According to maximum use hourage in maximum use hourage, concentrated maximum use hourage desired value and the concentrated maximum use hourage weights calculated set in the benchmark set;

Step 202: calculate gas station's equivalence charge volume, execution in step 203 and step 205 respectively according to the expection sales volume of gas station, the weight of electric automobile, per ton hundred kilometers power consumptions of electric automobile, the fuel consumption per hundred kilometers and the permeability of orthodox car;

Step 203: according to the charging amount of bearing of dispersion rate, dispersion charge volume apportionment ratio and equivalence charge volume zoning, gas station electrically-charging equipment;

Step 204:: according to the charging amount of bearing and the regional maximum use hourage zoning electrically-charging equipment peak load of regional electrically-charging equipment, execution in step 207;

Step 205: according to the charging demand of electrically-charging equipment in concentration ratio, concentrated charge volume apportionment ratio and the gas station's equivalence charge volume calculated set;

Step 206: according to electrically-charging equipment peak load in the charging demand of concentrating electrically-charging equipment and the concentrated maximum use hourage calculated set, execution in step 207;

Step 207: sending zone electrically-charging equipment peak load and concentrated electrically-charging equipment peak load;

Step 3: output area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

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