CN104077635A - Electric vehicle charging station charging optimization method based on photovoltaic power generation system - Google Patents

Abstract

The invention discloses a charging optimization method for an electric vehicle charging station based on a photovoltaic power generation system. The steps of the method include respectively predicting the current day's photovoltaic power generation characteristic curve, electric vehicle charging load and the number of electric vehicles; establishing a user price response model for electric vehicles and charging service price optimization model; establish and solve the objective function with the goal of minimizing the discarded amount of photovoltaic power generation, and carry out the operation of the charging station on the day according to the result of the charging service price obtained on the day; end the charging operation of the day, and correct the next one according to the actual situation of the day The daily charging load forecast and the inflection point value of the model corresponding to the charging service price of electric vehicle users; according to the revised parameter value, repeat the above steps to optimize the operation of the charging station on the second day. The invention can effectively overcome the impact of electric vehicle charging on the power grid, simultaneously improve the utilization rate of photovoltaics, and reduce the charging cost of electric vehicle users.

Description

A kind of electric automobile charging station charging optimization method based on photovoltaic generating system

Technical field

The present invention relates to a kind of charging optimization method, particularly relate to and a kind ofly based on photovoltaic generating system, be applicable to public domain electric automobile charging station charging optimization method.

Background technology

Pure electric automobile has the characteristic of zero-emission, becomes the important means that solves large-and-medium size cities environment and atmospheric pollution.Domestic main cities has started applying of pure electric passenger vehicle, mainly concentrates on taxi, government's car for public affairs aspect, and to individual, uses field expansion gradually.Because private car parking stall, large-and-medium size cities is few, the private present situation of using the care and maintenance system disappearance of pure electric automobile, the group customer pattern with private use characteristic has possessed good promotion prospect.Used for electric vehicle family under group customer pattern is mainly enterprises and institutions, the employee of colleges and universities, and charging electric vehicle infrastructure is mainly built in the centralized parking lot of internal institution, belongs to public domain electric automobile charging station.The access meeting of large-scale charging infrastructure is to Generation Side, power transmission network and power distribution network impact, both at home and abroad the research of this type of charging station is mainly concentrated in charging load power control method at present, to reduce maximum peak power, peak load shiftings etc. are as main control target, mainly to force to control charge power, the change duration of charging is means, electric automobile user can only accept regulation and control passively, can not initiatively select the duration of charging, do not set up the response model of pure electric automobile user to tou power price, do not consider electric automobile user's subjective desire and charging expense expenditure.In the business model participating in existing electric vehicle user, charging station operator, power supply enterprise, should more concerns the access of the new forms of energy such as bidirectional optimistic charging control strategy based on user's response and photovoltaic, meet simultaneously and reduce charging load to the impact of power distribution network and reduce charging expense, charging station operator and electric vehicle user are made a profit simultaneously, make whole business model sustainable development, improve the adaptability of charging infrastructure construction.

Therefore, need to provide a kind of charging optimization method that is applicable to public domain electric automobile charging station, with reduce charging electric vehicle on the impact of electrical network, improve photovoltaic utilization factor and reduce electric automobile user's charging cost.

Summary of the invention

The technical problem to be solved in the present invention is to provide and a kind ofly based on photovoltaic generating system, is applicable to public domain electric automobile charging station charging optimization method, to overcome the impact of charging electric vehicle on electrical network, improve photovoltaic utilization factor simultaneously, reduce electric automobile user's charging cost.

For solving the problems of the technologies described above, the present invention adopts following technical proposals;

Based on photovoltaic generating system be applicable to a public domain electric automobile charging station charging optimization method, the method comprises

S1, according to same day weather condition and electric automobile driving behavior, respectively the photovoltaic generation family curve on the same day, charging electric vehicle load and electric automobile quantity are predicted;

S2, according to the photovoltaic generation family curve of predicting in step S1 and charging electric vehicle load, set up electric automobile user price response model and charging service Price optimization model;

S3, the photovoltaic generation amount of the giving up minimum of take are set up objective function and solve as target, and according to the charging service price result on the same day of trying to achieve, carrying out charging station operation on the same day;

S4, finish charging operation on the same day, according to the charging load prediction of same day actual conditions correction next day and the flex point value of electric automobile user charging service price corresponding model;

S5, according to the parameter value of revising, repeating step S1 to S3, optimizes the charging station operation of second day.

Preferably, described step 1 comprises

S11, according to the weather condition prediction photovoltaic generation characteristic on the same day on the same day;

S12, according to electric automobile driving behavior prediction charging electric vehicle load, and based on the different electric automobiles hypothesis that duration and charge power be definite value of charging at every turn, determine the electric automobile quantity of day part initiation of charge, wherein, day part is to be divided into 24 periods by 24 hours, within one hour, is a period.

Preferably, described step 2 comprises

S21, obtain electric automobile user response parameter, according to the form of piecewise linear function, set up respectively peak-paddy period, peak-section, flat-paddy period electric automobile user price response model at ordinary times;

Put down at S22, the conceptual vector that defines respectively Pinggu, peak period and peak valley, peak, the price difference variable of Pinggu period, optimized variable as objective function, and according to the electric automobile quantity of electric automobile user price response model and day part initiation of charge, the method shifting according to day part uniform distribution obtains matching charging load expressions formula;

S23, according to the charging load expressions formula that the same day, photovoltaic generation family curve and you and matching obtained, obtain peak valley charging service price and implement the forward and backward photovoltaic amount of giving up expression formula;

S24, set up and take the equation that charging service price valley is variable, thereby determine charging service price basis value.

Preferably, the equation that described charging service price valley is variable to using reduce photovoltaic generation the amount of giving up as objective optimization, reduce the expense of operator's electrical network power purchase, simultaneously, operator is totally divided into the expense of minimizing according to certain ratio and electric automobile user, thereby reduces the total bulk charging expense of electric automobile group user.

Preferably, described step 3 comprises

S31, the photovoltaic generation amount of the giving up minimum of take are set up objective function as target, and wherein, Pinggu, peak period conceptual vector, charging service price basis value and peak valley, peak price difference flat, Pinggu period are optimized variable;

S32, arrange that charging service price bound, Pinggu, peak period are divided and the constraint condition of distribution capacity respectively;

S33, adopt the method for exhaustion to solve objective function, obtain that the photovoltaic generation amount of giving up Pinggu, peak period conceptual vector, charging service price basis value and peak valley, peak hour is flat, the price difference of Pinggu period, as the charging service price on the same day.

Beneficial effect of the present invention is as follows:

Technical scheme the present invention of the present invention can effectively overcome the impact of charging electric vehicle on electrical network, improves photovoltaic utilization factor simultaneously, reduces electric automobile user's charging cost.The present invention reaches good charging effect of optimization by formulating charging service price guidance electric automobile user's method than the method for control overhead; The present invention is directed to group customer and set up electric automobile user price response model, can reflect the responsiveness of electric automobile user to price; When optimizing, the present invention considered the continuity of single charging electric vehicle duration, realistic operation situation.

Accompanying drawing explanation

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail;

Fig. 1 illustrates the charging optimization method process flow diagram that is applicable to public domain electric automobile charging station of the embodiment of the present invention;

Fig. 2 illustrates peak-paddy period electric automobile user's of inventive embodiments response characteristic figure;

Fig. 3 illustrates the public domain electric automobile charging station operation process flow diagram of inventive embodiments;

Fig. 4 illustrates input and the Output rusults curve of inventive embodiments.

Embodiment

Below in conjunction with one group of embodiment and accompanying drawing, the present invention is described further.

The invention discloses the technical solution adopted for the present invention to solve the technical problems is a kind of charging optimization method that is applicable to public domain electric automobile charging station.As shown in Figure 1, the charging optimization method process flow diagram that is applicable to public domain electric automobile charging station for the embodiment of the present invention, according to prediction charging electric vehicle on same day load and photovoltaic generation family curve, method by objective function optimization is formulated charging service price on the same day, and guiding group user charges at public domain charging station.The charging station containing photovoltaic generating system of building Mou colleges and universities of take is example, below in conjunction with accompanying drawing and example, concrete grammar of the present invention is described further:

The first, before charging station operation on the same day starts, according to weather condition prediction on same day photovoltaic generation family curve on the same day the electric automobile duration T that at every turn charges _charg=2h and charge power P _charg=3kW is definite value, and determines the value of these two parameters, according to electric automobile driving behavior prediction charging electric vehicle load and according to following formula, determine the electric automobile quantity of day part initiation of charge.

$N_{\mathrm{EV},i}=\left\{\begin{array}{cc}{\tilde{P}}_{\mathrm{EV},i}/P_{\mathrm{ch}\arg },& i=1\\ {\tilde{P}}_{\mathrm{EV},i}/P_{\mathrm{ch}\arg }-N_{\mathrm{EV},i-1},& i\≠1\end{array}\right.$

The second, set up electric automobile user price response model and charging service Price optimization model.

1, obtain electric automobile user response characteristic parameter, set up respectively peak-paddy period, peak-section, flat-paddy period electric automobile user price response model at ordinary times, as shown in Figure 2.Peak-paddy period electric automobile user price response model of take is narrated its detailed step as example, and the establishment step of other two models is identical therewith.By the method for investigation, obtain the parameter of peak-paddy period electric automobile user response characteristic, comprise dead band threshold value Δ c _{pv, 1}=0, saturation region threshold value Δ c _{pv, 2}=1, the saturation value α of transferring user number percent _{pv, max}=100%, and obtain linear zone slope k _pv=α _{pv, max}/ (Δ c _{pv, 2}-Δ c _{pv, 1})=1, the expression formula that obtains thus peak-paddy period electric automobile user response characteristic is:

$\mathrm{\α}=\left\{\begin{array}{cc}0,& 0\≤\mathrm{\Δc}\≤{\mathrm{\Δc}}_{\mathrm{pv},1}\\ k_{\mathrm{pv}}(\mathrm{\Δc}-{\mathrm{\Δc}}_{\mathrm{pv},1}),& {\mathrm{\Δc}}_{\mathrm{pv},1}\≤\mathrm{\Δc}\≤{\mathrm{\Δc}}_{\mathrm{pv},2}\\ {\mathrm{\α}}_{\mathrm{pv},\max },& \mathrm{\Δc}\≥{\mathrm{\Δc}}_{\mathrm{pv},2}\end{array}\right.$

2, definition Pinggu, peak period conceptual vector: lab=[lab ₁, lab ₂lab ₂₄], work as lab _i, represent that the i period is the peak period of charging service price at=3 o'clock; Work as lab _i, represent that the i period is the section at ordinary times of charging service price at=2 o'clock; Work as lab _i, represent that the i period is the paddy period of charging service price at=1 o'clock; Work as lab _i, represent that the i period is night-time hours, without charging service price at=0 o'clock.Put down at definition peak valley, peak, the price difference Δ c of Pinggu period _pv, Δ c _pf, Δ c _fv.Above variable is the optimized variable of objective function.According to the parameter of electric automobile user price response model, obtain under the period dividing mode of Pinggu, peak of charging service price the peak period sum that initiation of charge vehicle distributes and at ordinary times section sum L _{p, all}, L _{f, all}, and peak, the length T of flat, paddy period _p, T _f, T _v, and according to the electric automobile quantity N of day part initiation of charge _{eV, i}, the following formula of substitution obtains matching charging load expressions formula:

${\tilde{P}}_{\mathrm{EV},i}^{\′}=\left\{\begin{array}{cc}{N}_{\mathrm{EV},i}^{\′},& i=1\\ P_{\mathrm{ch}\arg }\·(N_{\mathrm{EV},i-1}^{\′}+N_{\mathrm{EV},i}^{\′}),& i\≠1\end{array}\right.$

3, according to the photovoltaic generation family curve on the same day obtaining and the matching charging that step (2-2) obtains is loaded the photovoltaic amount of giving up expression formula after obtaining peak valley charging service price and implement according to following formula, if by following formula replace with obtain Q _vlostrepresent the photovoltaic amount of giving up before peak valley charging service price is implemented.

$Q_{\mathrm{Vlost}}^{\′}=1\·\underset{i}{\mathrm{\Σ}}({\tilde{P}}_{V,i}-{\tilde{P}}_{\mathrm{EV},i}^{\′}),i\∈\left\{i\right|({\tilde{P}}_{V,i}-{\tilde{P}}_{\mathrm{EV},i}^{\′})>0\}$

4, determine charging service price basis value, i.e. charging service price valley c _v.According to following formula, determine charging service price basis value, wherein N _p, N _f, N _vthe electric automobile user number of be illustrated respectively in peak, put down, charging the paddy period; c _p, c _f, c _vrepresent respectively the peak of charging service price, flat, valley, c _p=c _v+ Δ c _pv, c _f=c _v+ Δ c _fv; N _p, N _f, N _vthe electric automobile user number of be illustrated respectively in peak, put down, charging the paddy period; c ₀represent the charging uniforma price before charging service price is implemented; t ₀represent electrical network electricity price; Ratio represents overall minute proportional of electric automobile user.

(c _p·N _p+c _f·N _f+c _v·N _v)·T _charg·P _charg＝c ₀·(N _p+N _f+N _v)·T _charg·P _charg-ratio·t ₀·(Q _Vlost-Q' _Vlost)

Three, the foundation of objective function and solving.

1, take the photovoltaic generation amount of giving up minimum sets up objective function as target, and wherein peak, flat, three period conceptual vectors of paddy, charging service price basis value and peak valley, peak price difference flat, Pinggu period are optimized variable.Because photovoltaic generation diurnally carries out, and in example the service time of charging station be 7:00～18:00, therefore with matrix V=[v ₁, v ₂... v _m] the peak interval of time division result of 7:00～17:00 charging service price respectively, wherein m=11 represents the length of period on daytime, v _ipinggu, the peak attribute that represents the i period on daytime.

f＝minQ' _Vlost

2, constraint condition is set.

A) charging service price bound constraint: 0 < c _v< c _f< c _p< 1;

B) Pinggu, peak period is divided constraint, makes last T _chargindividual period attribute is identical:

${\mathrm{lab}}_{24-(T_{\mathrm{ch}\arg }-1)}={\mathrm{lab}}_{24-T_{\mathrm{ch}\arg }}=...={\mathrm{lab}}_{24};$

C) distribution capacity constraint, the charging electric vehicle load after charging service price is implemented should be within the service ability of charging station: $\max {\tilde{P}}_{\mathrm{EV},i}^{\&prime;}\&le;100\mathrm{kW}.$

3, coding adopts the method for exhaustion to solve objective function, obtains that the photovoltaic generation amount of giving up Pinggu, peak period conceptual vector, charging service price basis value and peak valley, peak hour is flat, the price difference of Pinggu period, as the charging service price on the same day.Optimize gained the same day charging service price period dividing mode and matching charging load curve as shown in Figure 4, the peak period is 7:00～10:00,0.71 yuan of peak valency; Section is 10:00～12:00 at ordinary times, 0.61 yuan of par; The paddy period is 12:00～18:00,0.31 yuan of paddy valency.

Four, charging station operation on the same day, its flow process as shown in Figure 3.

1, the charging service price result on the same day obtaining is published to charging reservation platform, charging station operation on the same day starts, electric automobile user, by various modes (as SMS, surfing Internet with cell phone, online computing), preengages charging according to the charging service price of different periods.

2, user drives into charging station by electric automobile and the initial time in the reservation period charges, and in reservation complete charge finish time period, user receives the SMS notification charging station that comes and pays the fees and electric automobile is sailed out of to charging station.

Five, work as end of day, charging station operator is according to the charging load prediction of the century charging load curve on the same day and actual photovoltaic generation curve correction next day, and according to electric automobile user the flex point value of real response situation correction electric automobile user charging service price response model to charging service price on the same day.Corrected parameter value is upgraded, before second day operation starts, got back to the first step.

Six, as shown in table 1, optimum results contrast on the same day.Every contrast under the embodiment of the present invention before and after charging service price guidance is as shown in the table, therefore by charging service price guidance, can reach and reduce the photovoltaic amount of giving up target, the electrical network purchase of electricity of operator and the peak value minimizing of charging electric vehicle load have been reduced simultaneously, reach the effect of peak clipping, reduced the impact of charging Load on Electric Power Grid.

Table 1 is used the method for the invention front and back Data Comparison

In sum, technical scheme the present invention of the present invention can effectively overcome the impact of charging electric vehicle on electrical network, improves photovoltaic utilization factor simultaneously, reduces electric automobile user's charging cost.The present invention reaches good charging effect of optimization by formulating charging service price guidance electric automobile user's method than the method for control overhead; The present invention is directed to group customer and set up electric automobile user price response model, can reflect the responsiveness of electric automobile user to price; When optimizing, the present invention considered the continuity of single charging electric vehicle duration, realistic operation situation.

Obviously; the above embodiment of the present invention is only for example of the present invention is clearly described; and be not the restriction to embodiments of the present invention; for those of ordinary skill in the field; can also make other changes in different forms on the basis of the above description; here cannot give all embodiments exhaustive, every still row in protection scope of the present invention of apparent variation that technical scheme of the present invention extends out or change that belong to.

Claims (5)

1. the charging of the electric automobile charging station based on a photovoltaic generating system optimization method, is characterized in that, the method step comprises

S1, according to same day weather condition and electric automobile driving behavior, respectively the photovoltaic generation family curve on the same day, charging electric vehicle load and electric automobile quantity are predicted;

S2, according to the photovoltaic generation family curve of predicting in step S1 and charging electric vehicle load, set up electric automobile user price response model and charging service Price optimization model;

S3, the photovoltaic generation amount of the giving up minimum of take are set up objective function and solve as target, and according to the charging service price result on the same day of trying to achieve, carrying out charging station operation on the same day;

S4, finish charging operation on the same day, according to the charging load prediction of same day actual conditions correction next day and the flex point value of electric automobile user charging service price corresponding model;

S5, according to the parameter value of revising, repeating step S1 to S3, optimizes the charging station operation of second day.

2. charging optimization method according to claim 1, is characterized in that, described step 1 comprises

S11, according to the weather condition prediction photovoltaic generation characteristic on the same day on the same day;

S12, according to electric automobile driving behavior prediction charging electric vehicle load, and based on the different electric automobiles hypothesis that duration and charge power be definite value of charging at every turn, determine the electric automobile quantity of day part initiation of charge.

3. charging optimization method according to claim 1, is characterized in that, described step 2 comprises

S21, obtain electric automobile user response parameter, according to the form of piecewise linear function, set up respectively peak-paddy period, peak-section, flat-paddy period electric automobile user price response model at ordinary times;

S22, the conceptual vector that defines respectively peak, flat, three periods of paddy and peak valley, peak are flat, the price difference variable of Pinggu period, optimized variable as objective function, and according to the electric automobile quantity of electric automobile user price response model and day part initiation of charge, the method shifting according to day part uniform distribution obtains matching charging load expressions formula;

S23, according to the charging load expressions formula that the same day, photovoltaic generation family curve and you and matching obtained, obtain peak valley charging service price and implement the forward and backward photovoltaic amount of giving up expression formula;

S24, set up and take the equation that charging service price valley is variable, thereby determine charging service price basis value.

4. charging optimization method according to claim 3, it is characterized in that, the equation that described charging service price valley is variable to using reduce photovoltaic generation the amount of giving up as objective optimization, reduce the expense of operator's electrical network power purchase, simultaneously, operator is totally divided into the expense of minimizing according to certain ratio and electric automobile user, thereby reduces the total bulk charging expense of electric automobile group user.

5. charging optimization method according to claim 1, is characterized in that, described step 3 comprises

S31, the photovoltaic generation amount of the giving up minimum of take are set up objective function as target, and wherein, Pinggu, peak period conceptual vector, charging service price basis value and peak valley, peak price difference flat, Pinggu period are optimized variable;

S32, arrange that charging service price bound, Pinggu, peak period are divided and the constraint condition of distribution capacity respectively;

S33, adopt the method for exhaustion to solve objective function, obtain that the photovoltaic generation amount of giving up Pinggu, peak period conceptual vector, charging service price basis value and peak valley, peak hour is flat, the price difference of Pinggu period, as the charging service price on the same day.