CN110443456A - A kind of control method for electric car charging net - Google Patents
A kind of control method for electric car charging net Download PDFInfo
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Abstract
The invention discloses a kind of control methods for electric car charging net, comprising: monitors system and electric car car-mounted terminal by fast charge station or obtains charging network data by emulation mode, calculates charging net operation level；Electric car car-mounted terminal data are obtained, user experience is calculated；Intelligent transportation acquisition and monitoring system data are obtained, traffic circulation disturbance degree is calculated；Power distribution network traffic control system data is obtained, power distribution network influence on system operation degree is calculated；Successively determine the weight of the charging each model of Running State computation model third layer respectively with entropy assessment；The weight of charging net operation level, user experience, network of communication lines influence on system operation degree and power distribution network influence on system operation four two layer models of degree is determined with analytic hierarchy process (AHP)；The integrated operation ability of charging net is obtained with the electric car charging net integration capability calculation method of level recursion；According to the calculated result of charging net service ability, preferred plan is screened, determines the weak link for filling operation of power networks, formulates the control program of charging net.
Description
Technical field
The present invention relates to electric cars to fill electrical network field more particularly to a kind of controlling party for electric car charging net
Method.
Background technique
Net charge as the mating infrastructure of electric car, the superiority and inferiority of Construction and operation directly influences ev industry
Development.Since charging net first stage of construction planning is unreasonable, electric car spatial and temporal distributions are uncertain, user's subjectivity selects not
The factors such as certainty cause the problems such as charging pile is idle, period of reservation of number is too long, traffic congestion, too low network voltage urgently
It is to be solved.Therefore, the service ability of electric car charging net can also generate one to user experience, traffic circulation, power distribution network operation
Determine the influence of degree.
So far, the research about electric car charging net service ability is also relatively preliminary, is largely focused on from filling
The angle of electric equipment, measures the operational energy efficiency of charging net, some another research concentrates on electric car charging net to power distribution network
In the calculating of influence.Do not fully consider that the coupling interaction of charging net and user, the network of communication lines and power distribution network close in current research
System can not reflect the actual conditions and weak link for filling operation of power networks comprehensively, still lack to the comprehensive of charging net service ability
And it specifically measures and calculates.It is thus impossible to effectively improve or make to power grid scheme is filled for the operation conditions of charging net
Fixed effective control strategy, results in the un-coordinated development problem of charging net and user, the network of communication lines, power distribution network.
Summary of the invention
The present invention provides it is a kind of for electric car charging net control method, based on charging net and user, the network of communication lines,
The coupled relation of power distribution network provides electric car charging net operation level, user experience, traffic circulation disturbance degree, distribution
Charging Running State computation model and electric car the charging net integrated operation capacity calculation model of net influence on system operation degree, from
And the operating status and weak link of comprehensive, multi-level embodiment charging net, and on this basis, the control of charging net is provided
Method improves its integrated operation ability, to realize electric car charging net and user, the coordinating and unifying of the network of communication lines, power distribution network
Development.It is described below:
A kind of control method for electric car charging net, the described method comprises the following steps:
It obtains fast charge station monitoring system and electric car car-mounted terminal data or charging network data is obtained by emulation mode,
Calculate charging net operation level；
Electric car car-mounted terminal data are obtained, user experience is calculated；
Intelligent transportation acquisition and monitoring system data are obtained, traffic circulation disturbance degree is calculated；
It obtains power distribution network and dispatches system data, calculate power distribution network influence on system operation degree；
Successively determine the weight of the charging each model of Running State computation model third layer respectively with entropy assessment；
Charging net operation level, user experience, network of communication lines influence on system operation degree and power distribution network fortune are determined with analytic hierarchy process (AHP)
The weight of four two layer models of row disturbance degree；
The integrated operation ability of charging net is obtained with the electric car charging net integration capability calculation method of level recursion；
According to the calculated result of charging net service ability, preferred plan is screened, determines the weak link for filling operation of power networks, system
The control program of fixed charging net.
Wherein, the calculated result according to charging net service ability, screens preferred plan specifically:
When it is newly-built fill power network planning scheme economy it is same or similar when, or charging net enlarging in area determines to new site
When plan, by comparing the net integration capability GA that charges, decision optimal charge net scheme；
When several charging net schemes synthesis ability GA are identical, according to the weight WB that analytic hierarchy process (AHP) determines, decision is determined
Person determines optimal in the highest model of second layer attention rate by comparing the quantized result of the model in second layer calculated result GG
Scheme.
Further, described that the comprehensive of charging net is obtained with the electric car charging net integration capability calculation method of level recursion
Close service ability specifically:
1) it determines charging net Operation class matrix, constructs membership function；
2) according to membership function and computation model standardized value, third layer model fuzzy matrix is determined by membership function,
In conjunction with its weight, second layer model fuzzy matrix is determined, in conjunction with second layer weight, determine first layer model fuzzy matrix；
3) using charging net Operation class matrix and third layer fuzzy matrix, the calculating knot of charging the second layer model of net is determined
Fruit；
4) using charging net Operation class matrix and second layer fuzzy matrix, the calculating knot of charging the first layer model of net is determined
Fruit.
The beneficial effect of the technical scheme provided by the present invention is that:
1, charging net and automobile user, the network of communication lines, power distribution network are considered in charging net service ability of the invention calculating
Coupling interactive relation, compared to conventional method, reflection that can be comprehensive, true, multi-level is charged net integrated operation ability, is embodied
The weak link of operation of power networks is filled, provides important references for charging net program decisions and the promotion of integrated operation ability；
2, the control method of the invention calculated based on charging net service ability, the weak link that can be effectively netted for charging
Improving Measurements are provided, for solve electric car charge net and user, the network of communication lines, power distribution network un-coordinated development, mismatch problem
Effective scheme is provided.
Detailed description of the invention
Fig. 1 is charging Running State computation model of the invention；
Fig. 2 is present invention charging net integrated operation capacity calculation flow chart；
Fig. 3 is the distribution form schematic diagram of membership function in the present invention；
Fig. 4 is the site distribution schematic diagram of fast charge net programme in the present invention；
Fig. 5 is the power distribution network topological structure schematic diagram that fast charge net accesses in the present invention；
Fig. 6 is fast charge Running State data normalization numeric distribution schematic diagram of the present invention；
Fig. 7 is the radar map of fast charge Running State calculated result of the present invention；
Fig. 8 is the integrated operation capacity calculation result schematic diagram of fast charge net programme of the present invention；
Fig. 9 is that fast charge net programme of the present invention influences schematic diagram to traffic circulation grade.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, embodiment of the present invention is made below further
Ground detailed description.
A kind of control method for electric car charging net, specifically includes that electronic vapour provided by the embodiment of the present invention
Vehicle charges Running State computation model (as shown in Figure 1) and the electric car charging net integration capability based on level recursion calculates
Method, process are as shown in Figure 2, the specific steps are as follows:
It charges Step 1: obtaining fast charge station monitoring system and electric car car-mounted terminal data or being obtained by emulation mode
Network data calculates charging net operation level；Include:
Step 11 determines average utilization AUR；
Firstly, the running time T at statistics fast charge stationfcsi；Later, in conjunction with the duration T of traffic data collection0, calculate each
The utilization rate UR at a fast charge stationi；Finally, the average value for calculating each fast charge station utilization rate obtains fast charge station average utilization AUR.
URi=Tfcsi/T0 (1)
In formula: N is electric car quantity.
Step 12 determines charging net average service radius ASR；
Automobile user i is obtained from charge requirement o'clock to the distance d at j-th of fast charge station by acquisition datai,j, calculating fills
Power grid average service radius ASR.
In formula: max (di,j) it is the maximum distance that user can arrive at the charging of i-th of fast charge station.
Step 13 determines charging net harmony δ.
Step 2: obtaining electric car car-mounted terminal data, user experience is calculated；Include:
Step 21 determines charge requirement satisfaction CDS；
Firstly, defining charging service factor betaiCan reflection automobile user obtain charging service, fill when user arrives at
Complete charging β in power stationi=1, the β when user fails to arrive at fast charge station in remaining course continuation mileagei=0；Later, by for electric vehicle
The practical charged state at family determines its charging service factor betai；Finally, charge requirement satisfaction CDS is calculated.
In formula: Z is the total number of users amount for having charge requirement.
Step 22 determines charging mileage increment Delta S；
I-th electric car is charged from departure place to fast charge station, is finally reached the destination, this trip process
Most short mileage is defined as Si, the most short trip mileage that i-th electric car is directly reached the destination from departure place is defined as
Si,0, according to collected data SiAnd Si,0Calculate charging mileage increment Delta S.
Step 23 determines that charging expends time Tch；
It is charged time Ts used according to i-th of useriWaiting time Tw with i-th of charge user at fast charge stationi, calculate
Automobile user charging expends time Tch。
Step 3: obtaining intelligent transportation acquisition and monitoring system data, traffic circulation disturbance degree is calculated, comprising:
Step 31 determines day operation index variation amount Δ TPI；
Traffic circulation index TPI is acquired by traffic system, fills forward and backward i-th of the section of operation of power networks in the traffic of period t
Run index TPIi,0 tAnd TPIi t, calculate day operation index variation amount Δ TPI, TPI and road speed, road etc. in emulation
Grade, the transforming relationship of congestion coefficient are as shown in table 1；
1 traffic noise prediction of table, congestion coefficient, passage speed and Operation class and TPI transforming relationship
Step 32 determines day congestion time variation amount Δ T；
Firstly, defining congestion in road factor alpha characterizes congestion in road situation, α can be determined according to category of roads L, when L is compared with Gao Lu
When section congestion, α value is 1；Otherwise α is 0；Determination fills the forward and backward i-th article of road of operation of power networks in the congestion system of t period as a result,
Number αi,0 tAnd αi t；Later, the time interval Δ t acquired according to road information, is calculated a day congestion time variation amount Δ T.
Step 33 determines maximum congestion mileage variation delta L；
The length l that each section of data is acquired according to traffic, is calculated maximum congestion mileage variation delta L.
Step 34 determines maximum congestion level variation delta CD.
Firstly, defining traffic congestion degree is CD；Secondly, t is calculated by congestion factor alpha and traffic circulation index TPI
Period fills the forward and backward traffic congestion degree CD of operation of power networkstAnd CDt,0；Become finally, calculating maximum congestion level according to formula (12)
Change amount Δ CD.
Δ CD (%)=max (CDt-CDt,0) (12)
Step 4: obtaining power distribution network traffic control system data, power distribution network influence on system operation degree is calculated；Include:
Step 41 determines load peak-valley difference variation delta P；
It arranges to obtain according to the collected data and fills operation of power networks forward and backward power distribution network daily load curve peak value and valley
Pmax 0、PmaxAnd Pmin 0、Pmin；Load peak-valley difference variation delta P is obtained by calculation；
Step 42 determines route heavy duty ratio increment Delta γl；
The ratio γ of route heavy duty is caused when obtaining filling the forward and backward total load peak value of operation of power networks by the data acquiredH 0With
γH, route heavy duty ratio increment Delta γ is calculatedl。
Step 43 determines transformer load rate change degree Δ TLR；
Firstly, filling the load factor S of operation of power networks i-th of transformer of forward and backward t moment by acquisition data acquisitioni,t 0And Si,t；
Secondly, determining the upper and lower boundary S of load factor when transformer operates normallyuAnd Sd, usual S in engineeringd=30%, Su=80%；
Later, defining i-th of transformer load rate change degree is Δ DSi,t, its size is determined by formula (15)；Finally, utilizing above-mentioned calculating
As a result transformer load rate change degree Δ TLR is obtained.
Step 44 determines node voltage offset variation amount Δ U；
Obtain filling the voltage per unit value U of i-th of power distribution network node of the forward and backward t moment of operation of power networks by acquisition datai,t 0、
Ui,t, then calculate node voltage offset variation amount Δ U.
Step 45 determines the out-of-limit quantity NU of node voltage.
Firstly, definition node voltage acceptance coefficient ε, allows by the per unit value of node voltage and for power distribution network safe operation
Voltage per unit value bound UmaxAnd UminDetermine node voltage acceptance coefficient ε, i.e., node voltage is in eligible state then ε=0, otherwise
Node voltage is in out-of-limit state ε=1；And then the operation data of power distribution network is combined, obtain node voltage before and after charging net layout
Acceptance coefficient εi,0、εi；Finally, the out-of-limit quantity NU of node voltage is calculated by formula.
Wherein, it is respectively U that setting power distribution network node voltage, which is safely operated bound,max=1.1, Umin=0.9.
Step 5: successively determining that charging Running State computation model third layer (as shown in Figure 1) is each respectively with entropy assessment
The weight of a model；Include:
The data of calculating are standardized by step 51；
The raw value being calculated is standardized as y using very poorization methodijk, make yijk∈[0,1]。
Step 52, the comentropy E for determining i-th of modelj i；
The standardized value that power grid scheme is filled according to m, is calculated the entropy of i-th of model according to the following formula.
Step 53 determines i-th of Model Weight；
In formula: njFor the quantity of corresponding third layer computation model under j-th of two layers of computation models.
Step 54, the weight vectors WC for determining j-th of two layers of computation modelsj, WCj=[wcj i]1×nj, and meet
Step 6: determining charging net operation level, user experience, network of communication lines influence on system operation degree with analytic hierarchy process (AHP) and matching
The weight of four two layer models of operation of power networks disturbance degree；Include:
S model is compared its significance level by step 61 two-by-two, constitutes judgment matrix As×s, s=4 in the present invention；
Wherein, the element a of ApqIt indicates the different degree comparison result of model p and model q, is respectively indicated with 1,3,5,7,9 same
It is important, strong important and extremely important etc. important, slightly important, obvious, and apq=1/aqp。
Step 62 determines two layers of computation model weight；
Its weight vectors WB=[wb is determined using geometric average methodj]1×s。
Step 63, consistency check.
Judgment matrix A integrally needs to meet logical consistency, and method of discrimination is as follows:
CR=CI/RI (23)
Wherein, λmaxFor the maximum eigenvalue of judgment matrix A；CI is judgment matrix approach index；RI is random consistency
Index, it is related with the order s of A；CR is consistency ratio.Wherein, CR0=0.1, RI=0.9.
As CR < CR0, i.e. consistency exports two layers of computation model weight in zone of reasonableness；Otherwise judgement square is reconfigured
Battle array, return step 61.
Step 7: the electric car charging net integration capability calculation method with level recursion obtains the integrated operation of charging net
Ability；Include:
Step 71 determines charging net Operation class matrix F；
Assuming that charging net service ability is divided into l grade, set V is constituted, then corresponding to its Operation class matrix is F1*l.Its
Element fvBe v-th of membership function be 1 when evaluation.Here, { splendid, good, fine, the poor, pole V=is set
Difference }, corresponding F=[100 80 60 40 20].
Step 72, building membership function；
The charging each grade membership function of net service ability is constructed in such a way that half is trapezoidal and triangle combines, and is such as schemed
Shown in 3.
Step 73, the fuzzy matrix for determining third layer computation model:
According to membership function and computation model standardized value, third layer computation model fuzzy matrix is determined by membership function
Rj=[ri,v]nj×l。
Wherein, ri,vIt is i-th of computation model in the degree of membership of v-th of grade of net that charges.
Step 74 determines second layer computation model fuzzy matrix；
According to third layer fuzzy matrix RjWith third layer weight WCj, determine the fuzzy matrix RG=[rg of the second layerj,v]s×l。
Wherein, rgj,vCalculation method be shown below.
Step 75, the fuzzy matrix for determining first layer computation model (charging net integrated operation ability)；
According to second layer fuzzy matrix RG and its weight WB, first layer computation model fuzzy matrix RA such as following formula institute is determined
Show.
Wherein:It isType fuzzy operator.
Step 76, the calculated result for determining the charging net computation model second layer；
Using matrix F and third layer fuzzy matrix RG, the calculated result matrix GG of the charging net second layer is determined.
GG=F × (RG)T (26)
Step 77, the calculated result for determining charging net computation model first layer.
Using matrix F and second layer fuzzy matrix RA, charging net integration capability quantized result GA is determined.
GA=F × (RA)T (27)
Step 8: screening preferred plan according to the calculated result of charging net service ability, the weakness for filling operation of power networks is determined
Link formulates the control program of charging net；Include:
Step 81, the best construction scheme for determining charging net；
When area is newly-built fill power network planning scheme economy it is same or similar when, or the enlarging of area charging net to new site into
When row decision, by comparing the net integration capability GA that charges, decision optimal charge net scheme；When several charging net schemes synthesis abilities
When GA is identical, according to the weight WB that step 6 analytic hierarchy process (AHP) determines, determine policymaker in the highest model of second layer attention rate,
Pass through the quantized result optimum scheme comparison of the model in GG.
Step 82 determines the weak link for filling operation of power networks；
Using charging the net second layer calculated result matrix GG, comparison charging net self-operating level, user experience,
The weak link of network of communication lines influence on system operation degree and power distribution network influence on system operation degree.
Step 83, according to charging net integrated operation ability weak link, provide charging net control method.
Due to filling electrical network weak link difference, the charging network control method taken difference, it is specific as follows shown in:
1) charge net operation level:
1. adjusting charger quantity according to charging station utilization rate situation, utilization rate is made to maintain zone of reasonableness；
2. the charging net for average service radius less than 5 kilometers should increase charging station quantity to meet user's daily trip
Demand；
3. adjusting charger number in charging station, charger quantity is made to match with the region electric automobile load demand；
2) user experience:
1. clustering to region automobile user charge requirement, adjustment charging website location distribution improves user's charging
Convenience；
2. the too long charging station of queuing time is guided or increased to automobile user with charging time minimum target
Charger number；
3) traffic circulation disturbance degree:
1. power network planning scheme is filled in improvement, avoid being laid out charging net in heavy congestion section；
2. taking charging guidance measure, guidance user avoids congested link；
3. being reconstructed to heavy congestion section；
4) power distribution network influence on system operation degree:
1. formulating electric car charging time-of-use tariffs strategy, with economic interests, guidance user fills in distribution network load paddy
Electricity, or the electric car charge and discharge of V2G technical controlling are used, have the function that peak load shifting；
2. reinforcing heavy-haul line load monitoring, heavy-haul line is transformed when necessary；
3. being planned again the charging station of transformer heavy duty after access, or the quantity of control charging station charger, In
When the above-mentioned measure of other factors constraint is not executable, dilatation can be carried out to the transformer that charging station accesses；
4. carrying out reactive compensation lower than qualified horizontal power distribution network node to voltage.
Simulation example:
The embodiment of the present invention is applied to urban area fast charge net programme service ability to calculate and control, in region
The distribution of fast charge net programme site as shown in figure 4, the power distribution network topological structure in the city as shown in figure 5, proving this with this
The feasibility and validity of method.
Acquire the urban area fast charge net related data, the operating status numerical value for the fast charge net being calculated through above-mentioned model
As shown in table 2.
2 fast charge Running State of table emulates data
Fast charge net third layer Model Weight is determined according to entropy assessment, obtains fast charge Running State data normalization numerical value such as
Shown in Fig. 6, so that the weight for obtaining the urban area fast charge net third layer model is as shown in table 3.
3 fast charge net third layer computation model weight of table
The second layer model of fast charge net determined according to analytic hierarchy process (AHP) from two angles of fast charge network operation business and traffic department
Weight is as shown in table 4.
Fast charge net second layer Model Weight under the different decision-makers of table 4
Later, the urban area determined using the electric car fast charge net integration capability calculation method based on level recursion
Fast charge net operation level, user experience, network of communication lines influence on system operation degree, power distribution network influence on system operation degree calculated result and fast charge
The calculated result difference that network planning draws schemes synthesis service ability is as shown in Figure 7 and Figure 8.Fig. 7 shows that this method can reflect fast charge
Superiority and inferiority of the net in terms of self-operating level, user experience, traffic circulation level and power distribution network operation level four, Fig. 8 table
The integrated operation ability of the bright available fast charge net of this method.
Secondly, being the decision and improvement weak link of fast charge net programme by fast charge net service ability calculated result
Guidance is provided.The calculated result of Fig. 8 shows that the integrated operation ability of programme three is most strong, therefore, is carrying out programme sieve
It is optimum implementation that selection scheme three is answered when selecting；Fig. 7 shows that the influence of fast charge net scheme a pair of power distribution network is smaller, and its other party
Face is performed poor, and scheme two can generate baneful influence to traffic circulation, and scheme four runs power distribution network and traffic circulation generates evil
Bad influence.
Finally, being directed to the weak link of fast charge net, the recommendation on improvement of fast charge net is determined.With the influence of scheme a pair of traffic circulation
Larger problem is illustrated, the friendship of traffic circulation grade and fast charge net scheme one by not being laid out fast charge net in comparison diagram 9
Logical Operation class distribution determines that the corrective measure of the program is the site for adjusting fast charge station G and J, to avoid congested link, or not
Change former scheme, but take charging guidance measure after building, to alleviate the influence to traffic circulation.Promoting to embody this method
The effect developed into the coordinating and unifying of electric car fast charge net, user, power distribution network and the network of communication lines.
The embodiment of the present invention to the model of each device in addition to doing specified otherwise, the model of other devices with no restrictions,
As long as the device of above-mentioned function can be completed.
It will be appreciated by those skilled in the art that attached drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention
Serial number is for illustration only, does not represent the advantages or disadvantages of the embodiments.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (3)
1. a kind of control method for electric car charging net, which is characterized in that the described method comprises the following steps:
It obtains fast charge station monitoring system and electric car car-mounted terminal data or charging network data is obtained by emulation mode, calculate
Charge net operation level；
Electric car car-mounted terminal data are obtained, user experience is calculated；
Intelligent transportation acquisition and monitoring system data are obtained, traffic circulation disturbance degree is calculated；
It obtains power distribution network and dispatches system data, calculate power distribution network influence on system operation degree；
Successively determine the weight of the charging each model of Running State computation model third layer respectively with entropy assessment；
Determine that charging net operation level, user experience, network of communication lines influence on system operation degree and power distribution network run shadow with analytic hierarchy process (AHP)
The weight of four two layer models of loudness；
The integrated operation ability of charging net is obtained with the electric car charging net integration capability calculation method of level recursion；
According to the calculated result of charging net service ability, preferred plan is screened, determines the weak link for filling operation of power networks, formulation is filled
The control program of power grid.
2. a kind of control method for electric car charging net according to claim 1, which is characterized in that described with layer
The electric car charging net integration capability calculation method of secondary recursion obtains the integrated operation ability of charging net specifically:
1) it determines charging net Operation class matrix, constructs membership function；
2) according to membership function and computation model standardized value, third layer model fuzzy matrix is determined by membership function, in conjunction with
Its weight determines second layer model fuzzy matrix, in conjunction with second layer weight, determines first layer model fuzzy matrix；
3) using charging net Operation class matrix and third layer fuzzy matrix, the calculated result of charging the second layer model of net is determined；
4) using charging net Operation class matrix and second layer fuzzy matrix, the calculated result of charging the first layer model of net is determined.
3. a kind of control method for electric car charging net according to claim 1, which is characterized in that the basis
The calculated result for the net service ability that charges screens preferred plan specifically:
When it is newly-built fill power network planning scheme economy it is same or similar when, or charging net enlarging in area carries out decision to new site
When, by comparing the net integration capability GA that charges, decision optimal charge net scheme；
When several charging net schemes synthesis ability GA are identical, according to the weight WB that analytic hierarchy process (AHP) determines, determine that policymaker exists
The highest model of second layer attention rate determines optimal side by comparing the quantized result of the model in second layer calculated result GG
Case.
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