CN102593902B - 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 Energy Equivalent

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 Energy Equivalent.

Background technology

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

Summary of the invention

The object of the invention is to, propose a kind of charging electric vehicle load prediction system and Forecasting Methodology thereof based on Energy Equivalent.

For achieving the above object, technical scheme provided by the invention is, a kind of charging electric vehicle load of utility prognoses system based on Energy Equivalent, it is characterized in that described prognoses system comprises: input module, processing module and output module, described processing module is connected with output module with input module respectively;

Described input module is used for the initial data of input 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 affects electrically-charging equipment load prediction, the achievement data that affects the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The described reference data that affects the factor of electrically-charging equipment load prediction comprises that benchmark permeability, benchmark dispersion rate, reference area maximum utilize maximum in hourage and benchmark set to utilize hourage;

The described achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights;

Described gas station data comprise that each gas station arrives the distance in each region and the expection sales volume of each gas station to distance, each gas station of each electrically-charging equipment;

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

Described processing module comprises that region maximum is utilized hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit, concentrated maximum utilizes hourage computing unit, region electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load is calculated unit;

Wherein, region maximum is utilized hourage computing unit, is disperseed charge volume apportionment ratio computing unit, dispersion rate computing unit and computing permeability unit to be connected with region electrically-charging equipment peak load calculating unit respectively;

Computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit and concentrated maximum utilize hourage computing unit to be connected with concentrated electrically-charging equipment peak load calculating unit respectively;

Described region maximum utilizes hourage computing unit for utilize hourage, region maximum to utilize hourage desired value and region maximum to utilize hourage weights zoning maximum to utilize hourage according to reference area maximum, and utilizes hourage to send to region electrically-charging equipment peak load region maximum and calculate unit;

Described 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 electrically-charging equipment peak load calculating unit, region;

Described dispersion charge volume apportionment ratio computing unit is used for to the distance in each region and each regional population's scale data, calculating dispersion charge volume apportionment ratio according to each gas station, and dispersion charge volume apportionment ratio is sent to electrically-charging equipment peak load calculating unit, region;

Described computing permeability unit is for calculating permeability according to benchmark permeability, permeability desired value and permeability weights, according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume, Bing Jiang gas station equivalence charge volume sends to respectively region electrically-charging equipment peak load and calculates unit and concentrated electrically-charging equipment peak load calculating unit;

Described 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 and concentrates electrically-charging equipment peak load to calculate unit;

Described concentrated charge volume apportionment ratio computing unit calculates concentrated charge volume apportionment ratio for arrive the distance of each electrically-charging equipment according to each gas station, and will concentrate charge volume apportionment ratio to send to and concentrate electrically-charging equipment peak load to calculate unit;

Described concentrated maximum utilizes hourage computing unit for utilizing hourage according to benchmark set maximum, concentrating maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage, and will concentrate maximum to utilize hourage to send to and concentrate electrically-charging equipment peak load to calculate unit;

Described region electrically-charging equipment peak load is calculated unit and is used for 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, according to the charging amount of bearing of region electrically-charging equipment and region maximum, utilize hourage zoning electrically-charging equipment peak load again, and region electrically-charging equipment peak load is sent to output module;

Described concentrated electrically-charging equipment peak load is calculated unit for calculating according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume the charging demand of concentrating electrically-charging equipment, according to the charging demand of concentrated electrically-charging equipment and concentrated maximum, utilize hourage to calculate concentrated electrically-charging equipment peak load again, and will concentrate electrically-charging equipment peak load to send to output module;

Described output module is used for viewing area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load, and for printing out region electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

A charging electric vehicle load of utility Forecasting Methodology based on Energy Equivalent, is characterized in that described 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 affects electrically-charging equipment load prediction, the achievement data that affects the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The described reference data that affects the factor of electrically-charging equipment load prediction comprises that benchmark permeability, benchmark dispersion rate, reference area maximum utilize maximum in hourage and benchmark set to utilize hourage;

The described achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights;

Described gas station data comprise that each gas station arrives the distance in each region and the expection sales volume of each gas station to distance, each gas station of each electrically-charging equipment;

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

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

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

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate dispersion rate;

According to each gas station, to the distance in each region and each regional population's scale data, calculate dispersion charge volume apportionment ratio;

According to benchmark permeability, permeability desired value and permeability weights, calculate permeability;

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate concentration ratio;

According to each gas station, to the distance of each electrically-charging equipment, calculate and concentrate charge volume apportionment ratio;

According to maximum in benchmark set, utilize hourage, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage;

Step 202: according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume, perform step respectively 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;

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

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

Step 206: according to concentrating charging demand and the concentrated maximum of electrically-charging equipment to utilize hourage to calculate concentrated electrically-charging equipment peak load, execution 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 basis to the impact of electrical network, also for charging electric vehicle facilities planning provides foundation.

Accompanying drawing explanation

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

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

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

Fig. 4 is that a certain gas station is equivalent to the equivalent charge volume distribution schematic diagram of concentrating electrically-charging equipment;

Fig. 5 is the charging amount of the bearing distribution schematic diagram that a certain gas station is equivalent to region electrically-charging equipment.

Embodiment

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

Fig. 1 is the charging electric vehicle load of utility prognoses system structure chart based on Energy Equivalent.In Fig. 1, the charging electric vehicle load of utility prognoses system based on Energy Equivalent provided by the invention comprises: input module, processing module and output module.Wherein, processing module is connected with output module with input module respectively.

Input module is used for the initial data of input 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 affects electrically-charging equipment load prediction, the achievement data that affects 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, choosing affects the factor of electrically-charging equipment load prediction and comprises economy/income level, area type, scale and position, electric automobile price, travel/continual mileage, vehicle laws of use/orderly management, charging price, electrically-charging equipment system, quality and totally 9 kinds of maintenance and other policy factors.For the factor that affects electrically-charging equipment load prediction, determine reference data, desired value and weights.

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

The achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights.

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

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

Processing module comprises that region maximum is utilized hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit, concentrated maximum utilizes hourage computing unit, region electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load is calculated unit.Wherein, region maximum is utilized hourage computing unit, is disperseed charge volume apportionment ratio computing unit, dispersion rate computing unit and computing permeability unit to be connected with region electrically-charging equipment peak load calculating unit respectively.Computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit and concentrated maximum utilize hourage computing unit to be connected with concentrated electrically-charging equipment peak load calculating unit respectively.

Region maximum utilizes hourage computing unit for utilize hourage, region maximum to utilize hourage desired value and region maximum to utilize hourage weights zoning maximum to utilize hourage according to reference area maximum, and utilizes hourage to send to region electrically-charging equipment peak load region maximum and calculate unit.

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 electrically-charging equipment peak load calculating unit, region.

Disperse charge volume apportionment ratio computing unit to be used for to the distance in each region and the calculating of each regional population's scale data, disperseing charge volume apportionment ratio according to each gas station, and dispersion charge volume apportionment ratio is sent to electrically-charging equipment peak load calculating unit, region.

Computing permeability unit is for calculating permeability according to benchmark permeability, permeability desired value and permeability weights, according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume, Bing Jiang gas station equivalence charge volume sends to respectively region electrically-charging equipment peak load and calculates unit and concentrated electrically-charging equipment peak load calculating unit.

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 and concentrates electrically-charging equipment peak load to calculate unit.

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

Concentrated maximum utilizes hourage computing unit for utilizing hourage according to benchmark set maximum, concentrating maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage, and will concentrate maximum to utilize hourage to send to and concentrate electrically-charging equipment peak load to calculate unit.

Region electrically-charging equipment peak load is calculated unit and is used for 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, according to the charging amount of bearing of region electrically-charging equipment and region maximum, utilize hourage zoning electrically-charging equipment peak load again, and region electrically-charging equipment peak load is sent to output module.

Concentrate electrically-charging equipment peak load to calculate unit for calculating according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume the charging demand of concentrating electrically-charging equipment, according to the charging demand of concentrated electrically-charging equipment and concentrated maximum, utilize hourage to calculate concentrated electrically-charging equipment peak load again, and will concentrate 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 for printing out region electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.Output module also demonstrates all types of regions (shopping centre, office building, residential area) and charging station for the form with element, click certain element and can eject a display window, show that computing module is to the partial data of the result of calculation of this element and the original input of element (sign, coordinate, type, scale), by dragging each element, can be well placed 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 the charging electric vehicle load of utility Forecasting Methodology flow chart based on Energy Equivalent.In Fig. 2, the charging electric vehicle load of utility Forecasting Methodology based on Energy Equivalent 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 affects electrically-charging equipment load prediction, the achievement data that affects 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 affects the factor of electrically-charging equipment load prediction comprises benchmark permeability α _f0, benchmark dispersion rate β _f0, reference area maximum utilizes hourage σ _d0utilize hourage σ with maximum in benchmark set _c0.

The achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights.Fig. 3 is the weight table of achievement data that affects the factor of electrically-charging equipment load prediction.In Fig. 3, having provided permeability weights, dispersion rate weights, region maximum utilizes hourage weights and concentrated maximum to utilize the concrete numerical value of hourage weights.And permeability desired value, dispersion rate desired value, region maximum in the present embodiment to utilize hourage desired value and concentrated maximum to utilize hourage desired value (be the x in Fig. 3 ₁-x ₉) can rule of thumb draw or utilize least square fitting to draw.

Gas station's data comprise that each gas station is to the distance r of each electrically-charging equipment _fC(ki), k gas station to the distance of i electrically-charging equipment; Each gas station is to the distance r in each region _fD(kj), k gas station to the distance in j region; The expection sales volume F (k) of each gas station.

Car data comprises the fuel consumption per hundred kilometers M (getting M=8 liter/hundred kilometer in the present embodiment) of the weight H (getting H=2 ton in the present embodiment) of electric automobile, per ton hundred kilometers of 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 the All population capacities in this region.

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

Step 201: utilize hourage, region maximum to utilize hourage desired value and region maximum to utilize hourage weights zoning maximum to utilize hourage according to reference area maximum.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 that the region maximum in j region is utilized hourage, σ _d0for reference area maximum is utilized hourage, g _i(i=1,2 ..., 9) for region maximum, utilize each under hourage and affect the weights of the factor of electrically-charging equipment load prediction, x _jibe that each of j region affects the desired value of the factor of electrically-charging equipment load prediction.

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate dispersion rate; 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 region, β _f0for benchmark dispersion rate, f _i(i=1,2 ..., 9) be that each under dispersion rate affects the weights of the factor of electrically-charging equipment load prediction, x _jibe that each of j region affects the desired value of the factor of electrically-charging equipment load prediction.

According to each gas station, to the distance in each region and each regional population's scale data, calculate dispersion charge volume apportionment ratio.Owing to this need to being disperseed charge capacity to be assigned near the region k of gas station, charge capacity will not be distributed in the region that exceeds certain distance.As shown in Figure 4, for this distance with interior region, here adopt and wait load apart from apportion design, owing to being that equivalent electric quantity is assigned to region from gas station here, therefore except the distance between consideration gas station and region, also need to consider the population size of zones of different, be that apportionment ratio is directly proportional to regional population's scale, be inversely proportional to distance.Therefore the computing formula that, is assigned to the dispersion charge volume apportionment ratio in j region 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 region, r _fD(kj) be k gas station to the distance in j region, J is the region number in setpoint distance, r _fDmaxfor setpoint distance, charge capacity will not be distributed in the region that exceeds this distance.

According to benchmark permeability, permeability desired value and permeability weights, calculate permeability.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 region, α _f0for benchmark permeability, e _i(i=1,2 ..., 9) be that each under permeability affects the weights of the factor of electrically-charging equipment load prediction, x _jibe that each of j region affects the desired value of the factor of electrically-charging equipment load prediction.

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate concentration ratio.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 region, β _f0for benchmark dispersion rate, f _i(i=1,2 ..., 9) be that each under dispersion rate affects the weights of the factor of electrically-charging equipment load prediction, x _jibe that each of j region affects the desired value of the factor of electrically-charging equipment load prediction.

According to each gas station, to the distance of each electrically-charging equipment, calculate and concentrate charge volume apportionment ratio.In near the concentrated electrically-charging equipment that this concentrated charge capacity need to be assigned to the k of gas station, the concentrated electrically-charging equipment that exceeds certain distance will not distribute charge capacity, as shown in Figure 5, for this distance, with interior concentrated electrically-charging equipment, still adopt here and wait load 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 k gas station to the distance of i concentrated electrically-charging equipment, I is the concentrated electrically-charging equipment number in setpoint distance, r _fCmaxfor setpoint distance, the concentrated electrically-charging equipment that exceeds this distance will not distribute charge capacity.

According to maximum in benchmark set, utilize hourage, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage.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 that the concentrated maximum of j concentrated electrically-charging equipment is utilized hourage, σ _c0for maximum in benchmark set is utilized hourage, h _i(i=1,2 ..., 9) for concentrating maximum to utilize each under hourage to affect the weights of the factor of electrically-charging equipment load prediction, x _jibe j electrically-charging equipment each affect the desired value of the factor of electrically-charging equipment load prediction.

Step 202: according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume.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 (the present embodiment equals 1378 liters of calculating by gasoline per ton), H is the weight of electric automobile, per ton hundred kilometers of power consumptions that p is electric automobile, the fuel consumption per hundred kilometers per ton that M is electric automobile.

Calculate after gas station's equivalence charge volume, perform step respectively 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 region electrically-charging equipment in j region, λ _fD(kj) be the dispersion charge volume apportionment ratio that k gas station is assigned to j region, 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:: utilize hourage zoning electrically-charging equipment peak load according to the charging amount of bearing of region electrically-charging equipment and region maximum.Its computing formula is:

P _Dmax(j)＝E _D(j)/σ _D(j) (10)

Wherein, P _dmax(j) be the region electrically-charging equipment peak load in j region, E _d(j) be the charging amount of bearing of the region electrically-charging equipment in j region, σ _d(j) be that the region maximum in j region is utilized hourage.

The region maximum that obtains each region is utilized after hourage, execution step 207.

Step 205: calculate the charging demand of concentrating electrically-charging equipment according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume.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 concentrating charging demand and the concentrated maximum of electrically-charging equipment to utilize hourage to calculate concentrated electrically-charging equipment peak load.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 that the concentrated maximum of i concentrated electrically-charging equipment is utilized hourage.

Obtain after the concentrated electrically-charging equipment peak load of each concentrated electrically-charging equipment execution 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 only the present invention's embodiment preferably, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in 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. the charging electric vehicle load of utility prognoses system based on Energy Equivalent, is characterized in that described prognoses system comprises: input module, processing module and output module, and described processing module is connected with output module with input module respectively;

Described input module is used for the initial data of input 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 affects electrically-charging equipment load prediction, the achievement data that affects the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The described reference data that affects the factor of electrically-charging equipment load prediction comprises that benchmark permeability, benchmark dispersion rate, reference area maximum utilize maximum in hourage and benchmark set to utilize hourage;

The described achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights;

Described gas station data comprise that each gas station arrives the distance in each region and the expection sales volume of each gas station to distance, each gas station of each electrically-charging equipment;

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

Described processing module comprises that region maximum is utilized hourage computing unit, dispersion charge volume apportionment ratio computing unit, dispersion rate computing unit, computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit, concentrated maximum utilizes hourage computing unit, region electrically-charging equipment peak load to calculate unit and concentrated electrically-charging equipment peak load is calculated unit;

Wherein, region maximum is utilized hourage computing unit, is disperseed charge volume apportionment ratio computing unit, dispersion rate computing unit and computing permeability unit to be connected with region electrically-charging equipment peak load calculating unit respectively;

Computing permeability unit, concentration ratio computing unit, concentrated charge volume apportionment ratio computing unit and concentrated maximum utilize hourage computing unit to be connected with concentrated electrically-charging equipment peak load calculating unit respectively;

Described region maximum utilizes hourage computing unit for utilize hourage, region maximum to utilize hourage desired value and region maximum to utilize hourage weights zoning maximum to utilize hourage according to reference area maximum, and utilizes hourage to send to region electrically-charging equipment peak load region maximum and calculate unit;

Described 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 electrically-charging equipment peak load calculating unit, region;

Described dispersion charge volume apportionment ratio computing unit is used for to the distance in each region and each regional population's scale data, calculating dispersion charge volume apportionment ratio according to each gas station, and dispersion charge volume apportionment ratio is sent to electrically-charging equipment peak load calculating unit, region;

Described computing permeability unit is for calculating permeability according to benchmark permeability, permeability desired value and permeability weights, according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume, Bing Jiang gas station equivalence charge volume sends to respectively region electrically-charging equipment peak load and calculates unit and concentrated electrically-charging equipment peak load calculating unit;

Described 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 and concentrates electrically-charging equipment peak load to calculate unit;

Described concentrated charge volume apportionment ratio computing unit calculates concentrated charge volume apportionment ratio for arrive the distance of each electrically-charging equipment according to each gas station, and will concentrate charge volume apportionment ratio to send to and concentrate electrically-charging equipment peak load to calculate unit;

Described concentrated maximum utilizes hourage computing unit for utilizing hourage according to benchmark set maximum, concentrating maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage, and will concentrate maximum to utilize hourage to send to and concentrate electrically-charging equipment peak load to calculate unit;

Described region electrically-charging equipment peak load is calculated unit and is used for 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, according to the charging amount of bearing of region electrically-charging equipment and region maximum, utilize hourage zoning electrically-charging equipment peak load again, and region electrically-charging equipment peak load is sent to output module;

Described concentrated electrically-charging equipment peak load is calculated unit for calculating according to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume the charging demand of concentrating electrically-charging equipment, according to the charging demand of concentrated electrically-charging equipment and concentrated maximum, utilize hourage to calculate concentrated electrically-charging equipment peak load again, and will concentrate electrically-charging equipment peak load to send to output module;

Described output module is used for viewing area electrically-charging equipment peak load and concentrated electrically-charging equipment peak load, and for printing out region electrically-charging equipment peak load and concentrated electrically-charging equipment peak load.

2. the charging electric vehicle load of utility Forecasting Methodology based on Energy Equivalent, is characterized in that described 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 affects electrically-charging equipment load prediction, the achievement data that affects the factor of electrically-charging equipment load prediction, gas station's data, each regional population's scale data and car data;

The described reference data that affects the factor of electrically-charging equipment load prediction comprises that benchmark permeability, benchmark dispersion rate, reference area maximum utilize maximum in hourage and benchmark set to utilize hourage;

The described achievement data that affects the factor of electrically-charging equipment load prediction comprises that permeability desired value, permeability weights, dispersion rate desired value, dispersion rate weights, region maximum utilize hourage desired value, region maximum to utilize hourage weights, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize hourage weights;

Described gas station data comprise that each gas station arrives the distance in each region and the expection sales volume of each gas station to distance, each gas station of each electrically-charging equipment;

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

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

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

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate dispersion rate;

According to each gas station, to the distance in each region and each regional population's scale data, calculate dispersion charge volume apportionment ratio;

According to benchmark permeability, permeability desired value and permeability weights, calculate permeability;

According to benchmark dispersion rate, dispersion rate desired value and dispersion rate weights, calculate concentration ratio;

According to each gas station, to the distance of each electrically-charging equipment, calculate and concentrate charge volume apportionment ratio;

According to maximum in benchmark set, utilize hourage, concentrate maximum to utilize hourage desired value and concentrated maximum to utilize the calculating of hourage weights to concentrate maximum to utilize hourage;

Step 202: according to the fuel consumption per hundred kilometers of per ton hundred kilometers of power consumptions of the weight of the expection sales volume of gas station, electric automobile, electric automobile, orthodox car and computing permeability gas station equivalence charge volume;

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; According to concentration ratio, concentrated charge volume apportionment ratio and gas station's equivalence charge volume, calculate the charging demand of concentrating electrically-charging equipment;

Step 204: utilize hourage zoning electrically-charging equipment peak load according to the charging amount of bearing of region electrically-charging equipment and region maximum; According to concentrating charging demand and the concentrated maximum of electrically-charging equipment, utilize hourage to calculate concentrated electrically-charging equipment peak load;

Step 205: 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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