CN102855527A - Economic running optimizing strategy for quick-change type electric car charging station - Google Patents

Abstract

The invention provides an economic running optimizing strategy for a quick-change type electric car charging station. The economic running optimizing strategy comprises the steps as follows: deducing the charging production capacity and the quantity of batteries required by cars entering a station based on the charging speed and the flow rate of the car entering the station; and setting that the charging production capacity is higher than the quantity of the batteries required by the cars entering the station in a certain allowance based on the running time range; and then charging the quantity of charging equipment to be put into service. With the adoption of the economic running optimizing strategy provided by the invention, the demand of the cars entering the station for changing the battery can be met, and the electric charge can be saved to the maximum.

Description

A kind of quick-changing type electric automobile charging station economical operation optimisation strategy

Technical field

The present invention relates to the electric vehicle engineering field, relate in particular to a kind of quick-changing type electric automobile charging station economical operation optimisation strategy.

Background technology

At present, the development of electric automobile charging station is very fast, there have been a plurality of fast changing battery formula charging stations to put into effect, the operation way that generally adopts is namely to insert namely to fill: after electric vehicle to be changed enters the station, such as existing battery of substituting the bad for the good, just change the battery of newly substituting the bad for the good, simultaneously immediately charging after pulling down with the battery of crossing, do not consider the economical operation scheduling based on Peak-valley TOU power price.

Runed latter stage on the same day, return under the unloading for vehicle of station will be for changing electricity next day with battery.At this moment, some quick-changing type charging stations can charge this batch battery during underestimate electricity price night, to save the electricity charge.Yet, during whole operation in, do not have corresponding economic operation strategy.

Summary of the invention

The object of the present invention is to provide a kind of quick-changing type electric automobile charging station economical operation optimisation strategy, change the historical data of electric vehicle flow according to entering the station, the Based Intelligent Control charging set is to the charging progress of battery, under the prerequisite that does not as far as possible cause vehicle to wait for, the charging task is moved to the low period of electricity price, thereby energy-conservation electric cost expenditure reaches charging station economical operation purpose.

In order to reach above purpose, the embodiment of the invention discloses a kind of quick-changing type electric automobile charging station economical operation optimisation strategy, may further comprise the steps:

Based on charging rate and vehicle pull-in flow, the charging productive capacity of deriving and the demand number of batteries that enters the station;

According to section working time, set charging productive capacity and be higher than the certain allowance of demand number of batteries that enters the station, obtain the charging equipment quantity that puts into effect.

Further, as a kind of preferred, allowance is zero.

Further, as a kind of preferred, if described working time, section was that electricity price is minimum, then the charging equipment quantity that puts into effect is not restricted.

The present invention changes the historical data of electric vehicle flow by entering the station, the Based Intelligent Control charging set under the prerequisite that does not as far as possible cause vehicle to wait for, moves to electricity price low period with the charging task to the charging progress of battery, thereby energy-conservation electric cost expenditure reaches charging station economical operation purpose.

Description of drawings

When considered in conjunction with the accompanying drawings, by the following detailed description of reference, can more completely understand better the present invention and easily learn wherein many advantages of following, but accompanying drawing described herein is used to provide a further understanding of the present invention, consist of a part of the present invention, illustrative examples of the present invention and explanation thereof are used for explaining the present invention, do not consist of to improper restriction of the present invention, wherein:

Fig. 1 is embodiment of the invention operation optimisation strategy process flow diagram;

Fig. 2 is the discharge diagram that enters the station Beijing Olympic Electric Transit charging station day;

Fig. 3 is rechargable battery semi-invariant and battery requirement curve map;

Fig. 4 is battery requirement and semi-invariant simulation result figure;

Fig. 5 is charging set current limliting stage power input curve and fitting result figure;

Fig. 6 is for namely inserting the mode of namely filling charging in lower day load chart;

Fig. 7 is intelligent operation/cutting mode charging in lower day load chart.

Embodiment

For above-mentioned purpose, feature and advantage can be become apparent more, the present invention is further detailed explanation below in conjunction with the drawings and specific embodiments.

Although more than described the specific embodiment of the present invention, but those skilled in the art is to be understood that, these embodiments only illustrate, those skilled in the art can carry out various omissions, replacement and change to the details of said method and system in the situation that do not break away from principle of the present invention and essence.For example, merge the said method step, then belong to scope of the present invention thereby carry out the identical function of essence according to the identical method of essence to realize the identical result of essence.Therefore, scope of the present invention is only limited by appended claims.

As shown in Figure 1, a kind of quick-changing type electric automobile charging station economical operation optimisation strategy may further comprise the steps:

S1, based on charging rate and vehicle pull-in flow, the charging productive capacity of deriving and the demand number of batteries that enters the station;

S2, according to section working time, set charging productive capacity and be higher than the certain allowance of demand number of batteries that enters the station, obtain the charging equipment quantity that puts into effect.

The embodiment of the invention is by analyzing the quick-changing type charging station and change electric rule and on the impact of battery requirement, studied and asked for the control the size algorithm of optimum limit value of charging equipment, proposed accordingly the economical operation optimisation strategy take peak load shifting as target.Be elaborated below in conjunction with figure.

1, the battery requirement is analyzed

It is the major advantage of quick-changing type electric automobile charging station soon that electric energy replenishes speed, and public vehicle in use adopts this kind mode more, such as bus, sanitation cart etc.The type charging station must configure the reserve battery of some, and adopts and namely insert the operation mode of namely filling: the reserve battery that Quick universal has been substituted the bad for the good behind the vehicle pull-in also begins charging with battery access charging set immediately with what pull down.Changing power and will designing and prove according to the flow that enters the station of quick-changing type charging station determines that the fair amount of charging set and reserve battery in the hope of reaching optimum matching, satisfies and enters the station the electric demand of changing of electric vehicle and possess certain allowance.Therefore, research economical operation optimisation strategy is at first tackled the vehicle pull-in flow and is analyzed.

Suppose that the charging station vehicle flow of marching into the arena obeys following formula:

d=D(t) (1)

In the formula, t is the time, and unit is hour, and t 0 namely represents 0 o'clock sharp of every day, and d is vehicle pull-in density, and unit is/hour.

Can obtain battery requirement formula by formula (1):

n _r(t)=∫D(t)dt (2)

If the charging duration of battery is T _c, reserve battery quantity is b ₀, the formula of then describing the battery semi-invariant is:

n _f(t)=b ₀+∫D(t-T _c)dt (3)

Then the battery allowance is:

n _d(t)=n _f(t)-n _r(t) (4)

The design of quick-changing type charging station should be satisfied the battery allowance at any time all greater than 0, and this and charging equipment quantity, reserve battery quantity have relation.Take Beijing Olympic Electric Transit charging station as example, 27 groups of reserve batteries, the average charge time of every Battery pack is about 2 hours, and the bus of regular working day (Mon-Fri) enters the station and changes the magnitude of current as shown in Figure 2.

Utilize formula (2) can try to achieve charging station battery every day requirement data, utilize formula (2) can ask for namely to insert and namely fill under the mode the semi-invariant of rechargable battery, the result as shown in Figure 3, article two, curve does not have joining, satisfying enters the station changes electric demand, two curves occur in 19: 30 at a distance of the narrowest place, and minimum value is 7 groups, and as seen rechargable battery has sufficient allowance.

2, the charging equipment impact of quantity on the battery relation between supply and demand that put into operation

Namely the slotting i.e. mode of filling is the battery altering strategy that the quick-changing type charging station generally adopts, and with behind the battery grafting charging equipment, utilizes the charging monitoring system automatically to start charging.The major advantage of this mode is that management is simple, can take full advantage of the reserve battery total amount and produce sufficient rechargable battery allowance.Yet, because enter the station flow and the magnitude of traffic flow of quick-changing type charging station have the property of being closely related, power load concentrates on daytime and covers the high crest segment of network load, if do not take rational optimisation strategy, just must cause higher grid electricity fee cost, also not meet the adjusting target of network load peak load shifting.

Period for electrical network peak and valley time policy divides, and the restriction charging equipment suitably reduces rechargable battery allowance in the quantity that puts into operation of crest segment peace section, the charging load can be moved to the paddy section, thereby reach the purpose of economical operation.Yet the charging duration of common electrokinetic cell is dozens of minutes at least, and the action need that starts charging equipment and be the battery charging just can have influence on rechargable battery semi-invariant after after a while, and then has influence on entering the station of electric vehicle and change electricity.Therefore, must research and analyse the relation between supply and demand of battery, utilize control algolithm to determine charging equipment put into operation quantity and boundary condition thereof.

If the initial time of certain period of time-of-use tariffs and termination are respectively t constantly ₁And t ₂, the period overall length is T _s, changed electricity the same day for the 1st time and constantly be t ₀, the charging equipment quantity limit value that puts into operation is the m platform.The impact that quantity produces because the restriction charging equipment puts into operation will continue up to charging process and finish, so the minimum point of battery allowance occurs in t ₂+ T _cConstantly, this moment, the battery requirement was calculated by formula (2):

$n_r({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)=\underset{t=t_0}{\overset{{\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c}{\&Integral;}}D\left(t\right)\mathrm{dt}---\left(5\right)$

The rechargable battery semi-invariant is:

$n_f({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)=b_0+\underset{t={\mathrm{<figure-callout\; id="0"\; label="t"\; filenames="HDA00002106978800021.png,HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_0+T_c}{\overset{t_1}{\&Integral;}}D(t-T_c)\mathrm{dt}+\underset{t=t_1}{\overset{{\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c}{\&Integral;}}\frac{m}{T_c}\mathrm{dt}---\left(6\right)$

Formula (6) variable is substituted, obtains:

$n_f({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)=b_0+\underset{x=t_0}{\overset{t_1-T_c}{\&Integral;}}D\left(x\right)\mathrm{dx}+\frac{T_s+T_c}{T_c}---\left(7\right)$

Then the battery allowance is:

$n_d({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)=n_f({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)-n_r({\mathrm{<figure-callout\; id="2"\; label="t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">t</figure-callout>}}_2+T_c)$

$=b_0-\underset{x=t_1-{\mathrm{<figure-callout\; id="2"\; label="T\; c\; t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">T</figure-callout>}}_c}{\overset{t_{}}{\&Integral;}}D\left(x\right)\mathrm{dx}+\frac{T_s+T_c}{T_c}\&CenterDot;m---\left(8\right)$

Make formula (8) equal 0, try to achieve the put into operation minimum value (Optimal Boundary) of quantity limit value of charging equipment:

$m_{\mathrm{opt}}=(\underset{t=t_1-{\mathrm{<figure-callout\; id="2"\; label="T\; c\; t"\; filenames="HDA00002106978800031.png"\; state="\{\{state\}\}">T</figure-callout>}}_c}{\overset{t_{}}{\&Integral;}}D\left(t\right)\mathrm{dt}-b_0)\&CenterDot;\frac{T_c}{T_s+T_c}---\left(9\right)$

Formula (9) possesses versatility, can calculate accordingly to set the put into operation optimum limit value of quantity of charging equipment in the period.By formula as can be known, but the more sufficient then charging equipment of the reserve battery quantity amplitude of accommodation is larger, and effect of optimization is just more obvious.

The applied analysis of 3, economical operation optimisation strategy

Effect as an example of Beijing Olympic Electric Transit charging station example to the economical operation optimisation strategy carries out simulating, verifying, comprises two aspects: the peak load shifting effect of the feasibility of operation prioritization scheme and charging load.

The optimum limit value of quantity finds the solution and verification 3.1 charging set puts into operation

Table 1 is Beijing's peak and valley time sales rate of electricity table, and continuous 8 hours of the late into the night and morning is the paddy section, and other times then are crest segment peace section.According to the division of Peak-valley TOU power price period, can obtain the put into operation optimum limit value of quantity of a plurality of charging sets according to formula (9).Take first crest segment as example, the time be 10 o'clock to 15 o'clock, make b ₀=27, T _c=2, T _s=5, the flow that enters the station shown in Figure 2 is piecewise function and is constant, is easy to calculate the put into operation optimum limit value of quantity of charging set:

$m_1=(\underset{t=8}{\overset{10.5}{\&Integral;}}7.5\mathrm{dt}+\underset{t=10.5}{\overset{11.5}{\&Integral;}}6\mathrm{dt}+\underset{t=11.5}{\overset{17}{\&Integral;}}7.5\mathrm{dt}-27)\&CenterDot;\frac{2}{7}$

$=11$

Therefore, in first crest segment, the restricted number that puts into operation of charging set is 11 platforms after, be down to minimum at the power consumption that satisfies this section under the prerequisite of changing electric demand that enters the station.

The 2nd crest segment be from 18 o'clock to 21 o'clock, is 22: 30 because the charging duration is 2 hours and last frequency, thus should be in the period charging set quantity limit value that puts into operation be:

$m_1=(\underset{t=16}{\overset{17.5}{\&Integral;}}7.5\mathrm{dt}+\underset{t=17.5}{\overset{19.5}{\&Integral;}}10\mathrm{dt}+\underset{t=19.5}{\overset{22.5}{\&Integral;}}6\mathrm{dt}-27)\&CenterDot;\frac{2}{4.5}$

$=9$

The control strategy of all the other periods and limit value be referring to table 2, and table two-story valley section has also limited the quantity that puts into operation of charging set, and purpose is to reduce to charge the peak value of load.

Table 1 Beijing peak and valley time sales rate of electricity table (summer, part)

Annotate: general industry and commerce, 1 ~ 10kV.

The table 2 charging set quantity limit value table that puts into operation

Annotate: keep referring to finish existing charging task, but do not start new charging task.

Write simulated program optimum limit value is carried out verification, the emulation cycle is 1 day (1440 minutes), and stepped intervals is 1 minute, if the electric automobile quantity etc. electricity to be changed is b, in running order charging set quantity is c, and the number of batteries that has charged is d, time schedule is t, and simulation process is as follows:

1) initialization relevant data and generate the electric automobile timetable that enters the station according to Fig. 1.

2) time schedule t=t+1, whether have electric automobile enter the station, be b=b+1 then if checking.

3) judge segment type when which kind of this belongs to constantly, then according to table 2 the put into operation limit value of quantity of charging set is set.

4) state of the every Battery pack of inspection: charging progress increases 1 as just charging then; As reach the charging duration then be set to the completion status of charging; Finish then d=d+1 such as charging; As etc. to be charged and control strategy be not to keep then to be set to charged state.

5) the in running order charging set quantity of statistics then at first stops the minimum charging set of battery charging progress as surpassing limit value, and state is set to wait for, continues to carry out the 5th step as still surpassing limit value.

6) whether progress t reaches setting value the supervision time, is then to stop and Output rusults, otherwise jumps to for the 2nd step.

Simulation result exerts an influence to the battery semi-invariant when for the first time being adjusted at 12 as shown in Figure 4, allowance is constantly reduced and reaches minimum value in the time of 17; Be adjusted in about 19: 20 and exert an influence the second time, reaches minimum value 22: 30 allowances, and produce intersection point with the requirement curve, finished the electric task of changing of very end of the train bus, the same day do not occur changing electric delay.

Therefore, the optimum limit value that formula (9) calculates is more accurate, takes full advantage of the quantity of charging station reserve battery, has farthest limited the charging equipment quantity that puts into operation.In actual motion, can suitably improve as the case may be limit value to increase the allowance of rechargable battery, effectively guarantee to enter the station the electric demand of changing of vehicle.

3.2 economical operation optimisation strategy simulating, verifying

Be the effect of accurate Simulation Evaluation economic operation strategy, this paper has carried out statistical study according to the field measurement data (in September, 2010) of Beijing Olympic electric bus charging station, has studied the describing method of charging set power input.The course of work of charging set comprises constant current voltage limiting and two stages of constant voltage and current limiting, and constant current voltage limiting stage power input substantially constant reduces gradually and constant voltage and current limiting stage power input is stepped, until shut down.Adopt least square method that the charging set power input in constant voltage and current limiting stage is carried out curve fitting, the results are shown in Figure 5, describe formula and see Table 3.The method of operation is that 6 1# charging sets and 1 2# charging set are Battery pack charging jointly, and about general power 40kW, total idling consumption is 0.63kW.

Table 3 charging set power input is described formula

Annotate: t is the duration in constant voltage and current limiting stage, and unit is minute.

The simulating, verifying of economical operation optimisation strategy need to be added up whole day active power, and calculates the electricity charge according to the electricity price that table 1 provides.Emulation mode is consistent with preamble with step, and the method for operation comprises namely inserting namely fills and two kinds of intelligent operation/cuttings.Simulation result is seen Fig. 6 ~ Fig. 7 and table 4.

Load curve by comparison diagram 6 and Fig. 7 as can be known, take charging set intelligent operation/cutting mode after, the crest segment load reduces and paddy section load enlarges markedly.The statistics that table 4 is listed shows: by stepless control, part charging load is passed to flat section from crest segment, passes to paddy section at night from flat section again, and a flat section electric weight has and reduces by a small margin and the crest segment electric weight is able to decrease, total electric weight basis equalization of three class periods, the control effect is remarkable.In addition, although intelligent operation/cutting decreases charging set standby total losses, amplitude is very little, so the day electric weight of two kinds of methods of operation is very nearly the same.Yet, taking the electricity charge that save every day after the economical operation optimisation strategy is 1359.92 yuan, the range of decrease is up to 19.5%, because the emulation statistics is the charging set power input, as count power supplying efficiency and affect that then the 10kV high-pressure side charging range of decrease will be above 20%, take full advantage of Peak-valley TOU power price in the preferential policy of paddy section, met the purpose of design of economical operation optimisation strategy.

Table 4 charging station daily power consumption and electricity charge comparing result

Although more than described the specific embodiment of the present invention, but those skilled in the art is to be understood that, these embodiments only illustrate, those skilled in the art can carry out various omissions, replacement and change to the details of said method and system in the situation that do not break away from principle of the present invention and essence.For example, merge the said method step, then belong to scope of the present invention thereby carry out the identical function of essence according to the identical method of essence to realize the identical result of essence.Therefore, scope of the present invention is only limited by appended claims.

Claims (3)

1. a quick-changing type electric automobile charging station economical operation optimisation strategy is characterized in that, may further comprise the steps:

Based on charging rate and vehicle pull-in flow, the charging productive capacity of deriving and the demand number of batteries that enters the station;

According to section working time, set charging productive capacity and be higher than the certain allowance of demand number of batteries that enters the station, obtain the charging equipment quantity that puts into effect.

2. quick-changing type electric automobile charging station economical operation optimisation strategy according to claim 1 is characterized in that, described allowance is zero.

3. quick-changing type electric automobile charging station economical operation optimisation strategy according to claim 1 is characterized in that, if described working time, section was that electricity price is minimum, then the charging equipment quantity that puts into effect is not restricted.

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